HANDBOOK TO THE IOT LARGE-SCALE PILOTS PROGRAMME

From WikiName
Jump to: navigation, search

IoT LSP handbook contains the reference terminology facilitating cross fertilisation among all the Large-Scale Pilots (LSPs) calls, to ensure the use of a common terminology in addressing the technical (protocols, formats, APIs, etc.) and non-technical (business models, testing and validation methodologies, regulatory framework, etc.) issues. This is implemented offline and will be transfer online (i.e. web platform for exchange/community building) during the next phase.

The IoT LSP handbook aims at disseminating knowledge about IoT terminology among the IoT European Large-Scale Pilot Programme projects and IoT stakeholders at large, and at providing easy access to a large range of technical and non-technical IoT. The document is a reference work, including a collection of terms, that is intended to provide ready reference in the field of IoT technologies and applications. The document is designed to be easily consulted and provide quick answers in the IoT area. The IoT LSP handbook addresses will be expanded and revised during the lifetime of the IoT European Large-Scale Pilot Programme.

Glossary

Shortcuts to the glossary

0-9 A B C D E F G H I J K L M N O P Q R S T U V X Y Z


0-9


2G: Second-generation digital cellular networks used by mobile phones, designed as a replacement for analogue first-generation radio (1G). Designed primarily for voice using digital standards.
Keywords: Network communication layer

3G: Third-generation wireless mobile telecommunications technology required by International Mobile Telecommunications for the year 2000 (IMT-2000) standard from International Telecommunication Union (ITU) to support at least 200 kbps at peak rate. First mobile broadband utilizing IP protocols - added text and image messaging to voice phone calls
Keywords: Network communication layer

5G: The technology designation of the next generation mobile network. Standardization work through ITU-R / IMT-2020 is expected to be completed by 2020, however, it will take several years before "all" expectations are met and widely available (e.g. implementation of frequencies up to 30 GHz). There are high expectations and requirements with respect to speeds, latency and energy efficiency. A very large increase in capacity and much faster internet on mobile phones is expected. The frequency bands are not finally established; however, the EU advisory body Radio Spectrum policy Group proposes three pioneer frequency bands for fifth generation mobile services: 694-790 MHz, 3.4-3.8 GHz, and 24.25-27.5 GHz [Ref 1][Ref 2][Ref 3].
Keywords: Network communication layer

5G Infrastructure Public-Private Partnership (5G PPP): The 5G PPP is a joint initiative between the European Commission and the ICT industry. The goal is to deliver solutions, architectures, technologies and standards for the ubiquitous next generation communication infrastructures to maintain and strengthen the global technological lead [Ref 4].
Keywords: Other cross-cutting concepts

5G New Radio (5G NR): 5G NR is a new air interface being developed for 5G. It is being developed to support the wide variety of services, devices and deployments 5G will encompass, and across diverse spectrum [Ref 5].
Keywords: Network communication layer, Wireless

A-C

A


A Root of Trust:An immutable boot process within an IoT system based on unique identifiers, cryptographic keys and on-chip memory, to protect the device from being compromised at the most fundamental level. The Chain of Trust extends the Root of Trust into subsequent applications and use cases. Given that IoT systems rely on a large number of devices that collect and process information, it is paramount to ensure their credibility so that they are honest and leverage correct outputs.[Ref 6].
Keywords: AI, IoT, Other cross-cutting concepts

AAL: See Ambient Assisted Living.

Accountability: The obligation of an individual or organization to account for its activities, to accept responsibility for them, and to disclose their results in a transparent manner. It also includes responsibility for money or other property entrusted to them [Ref 7].
Keywords: AI, IoT, Other cross-cutting concepts

Active and healthy ageing: Active ageing means helping people stay in charge of their own lives for as long as possible as they age and, where possible, to contribute to the economy and society [Ref 8].
Keywords: Application Layer, Other cross-cutting concepts.

Actuators: Specially kind of IoT devices capable of executing actions.
Keywords: Other cross-cutting concepts.

Adaptive Gateway: A gateway which can adapted to different standards and make it easy to exchange data [Ref 9].
Keywords: Physical layer.

Advanced Driver Assistance System (ADAS): Advanced driver assistance systems (ADAS) are vehicle-based intelligent safety systems. These integrated in-vehicle or infrastructure-based systems aid the human driver with either steering, braking or accelerating by including intelligent speed adaptation and advanced braking systems[Ref 10].
Keywords: Application Layer.

Adverse climatic event: Weather conditions, such as frost, storms and hail, ice, heavy rain or severe drought, which can be considered to be a natural disaster [Ref 11].

Ageing Well: A better quality of life and better health through prolonged independent living; active ageing at work ensuring that older workers can continue to improve and practise their skills; and increased social participation [Ref 12].
Keywords: Other cross-cutting concepts, Application Layer.

Agile: Agile software development describes a set of values and principles for software development under which requirements and solutions evolve through the collaborative effort of self-organizing cross-functional teams. It advocates adaptive planning, evolutionary development, early delivery, and continuous improvement as well as encouraging rapid and flexible response to change. These principles support the definition and continuing evolution of many software development methods [Ref 13].
Keywords: Other cross-cutting concepts.

Agri-food logistics: The economic and commercial activity related to the transportation of Agrifood goods to customers. The application of digital technologies such as IoT to agrifood logistics enables the overall logistics operation to be optimized by contributing real-time virtualization, logistics connectivity and logistics intelligence.
Keywords: Application Layer, Farming.

Agricultural activity: Tthe production, rearing or growing of agricultural products including harvesting, milking, breeding animals and keeping animals for farming purposes; or maintaining the agricultural area in a state which makes it suitable for grazing or cultivation without any particular preparatory action going beyond usual agricultural methods and machinery based on criteria to be defined by member states on the basis of a framework established by the Commission; orcarrying out a minimum activity to be established by member states on agricultural areas naturally kept in a state suitable for grazing or cultivation [Ref 11]

Ambient assisted living: Ambient Assisted Living (AAL) comprises interoperable concepts, products and services, that combine new information, communication technologies (ICT) and social environments with the aim of improving and increasing quality of life for people of all ages. AAL can best be understood as an age-based assistance system for a healthy and independent life catering to the varying abilities of its users. It also outlines AAL as being primarily concerned with the individual in his or her immediate environment by offering user-friendly interfaces for all sorts of equipment in the home and outside, taking into account that many older people have impairments in vision, hearing, mobility or dexterity [Ref 14].
Keywords: Other cross-cutting concepts, Application Layer, Physical layer.

Ambient Intelligence: An emerging discipline that brings intelligence to our everyday environments and makes those environments responsive to us [Ref 15].
Keywords: Application Layer.

Ambient Localization: Localization is the process of adapting a product to a particular country, market or region [Ref 16].
Keywords: Application Layer.

Ambient sensing: Ambient sensing refers to the set of devices embedded/hidden in a network using contextual information and enabling the use of artificial intelligence to support people carrying out their day-to-day activities. This concept goes back to the 1990s where these tasks were performed by a combination of consumer electronics, telecommunication protocols and computing. As IoT was booming, devices grew smaller and more powerful, enabling the use of greater amounts of sensing devices and, therefore, data, resulting in the development of the smart home, smart buildings, and the smart office [Ref 17].
Keywords: Application Layer.

Alliance for Internet of Things Innovation (AIOTI): AIOTI was established in 2016 and aim to strengthen the dialogue and interaction among IoT players in Europe, and to contribute to the creation of a dynamic European IoT ecosystem to speed up the take up of IoT. Members of the Alliance include key IoT industrial players (large companies, SMEs and start-ups) as well as European research centres, universities, associations and public [Ref 18].
Keywords: Other cross-cutting concepts.

Application Entity (AE):AE is an entity in the application layer that implements an M2M application service logic. Each application service logic can be resident in a number of M2M nodes and/or more than once on a single M2M node. Each execution instance of an application service logic is termed an AE and is identified with a unique AE-ID [Ref 19].
Keywords: Application Layer

Application Programming Interface (API): An API is a set of subroutine definitions, protocols, and tools for building application software. In general terms, it is a set of clearly defined methods of communication between various software components. A good API makes it easier to develop a computer program by providing all the building blocks, which are then put together by the programmer. An API may be for a web-based system, operating system, database system, computer hardware or software library [Ref 20].
Keywords: Abstraction Layer

Architecture: In reference to information technology, the architecture covers the overall system design and the logical and physical interrelationships between its components. The architecture specifies the HW, SW, access methods and protocols used throughout the system. It is also used as a description of framework and guidelines including development methodologies, modelling tools and organizational structures to build new systems. The architectural framework for the IoT includes descriptions of various IoT domains, definitions of IoT domain abstractions and identification of commonalities between different IoT domains. The IoT architecture will grow in an evolutionary way from a variety of separate contributions. The main challenges for the IoT architecture are the complexity and cooperative work for developing, adopting and maintaining an effective cross-industry technology reference architecture that will allow for true interoperability and ease of deployment [Ref 21][Ref 22][Ref 23].
Keywords: Other cross-cutting concepts.

Artistic practices: A practice is the actual application or use of an idea, belief, or method, as opposed to theories relating to it. Artistic practices, much like engineering and scientific practices, produce knowledge in research processes. David Thomas describes art practice as a way of researching through the practice of making art. Such making is not just doing, but is a complex informed physical, theoretical and intellectual activity where public and private worlds meet. Moreover, artistic practice, as research-in-the making, constitutes a betrayal of prevailing cultural assumptions, an interminable renouncement of normalized research representations in favour of the contingent problematic that emerges during arts practice. The practice of the arts is central in artistic research as it embodies ideas that are given form in the process of making artwork. In this context, there is a field of artistic practice contributing to innovation in ICT technologies. It emerged out of the crossover of several fields of art and science having technology as a common ground. In this intersection, new digital technologies and applications are the main outcome. In its realm, creativity in digital technologies often finds natural ways to direct proof-of-concept. It is exactly here that the field finds its contact points with neighbouring fields of research and practice, namely industrial partners. The achievement of concrete practical outcomes is one of the most important aspects when it comes to technological transfer to society. Artistic practices in technological contexts, such as IoT, are naturally close-to-market as technology is their medium of expression [Ref 24][Ref 25][Ref 26][Ref 27].
Keywords: Other cross-cutting concepts.

Augmented Reality (AR): The real-time view of the real physical world with the ability to add audio-visual effects (unlike virtual reality (VR) which replaces the real world with simulations). These audio-visual effects are virtual means/enhancements integrated with the real-world objects to create added value. Highlighting in the form of graphics, audio or text can be used to catch users' attention and indirectly inform subsequent actions [Ref 21].
Keywords: Other cross-cutting concepts.

Authentication: The act of confirming the truth of an attribute of an entity or a single piece of data by using passwords, PINs, smart cards, digital certificates, or biometrics to sign in. In contrast with Identification, Authentication is the process of actually confirming the Identity of a device or confirming that data arriving or leaving are genuine and have not been tampered with or forged [Ref 28].
Keywords: AI, IoT, Other cross-cutting concepts

Authorization: The function of specifying access rights to resources and ensuring that any request for data or control of a system is managed within these policies. Authorization mechanisms tend to be centralized, which may be a challenge in IoT systems that tend to be increasingly decentralized, with- out an authority involved. Whatever the degree of democratized authorization, where more entities can grant permissions, the authorization system must be consistent, persistent and attack resistant [Ref 29].
Keywords: AI, IoT, Other cross-cutting concepts

Automated Driving Systems: Automated Driving Systems, also known as self-driving cars, are vehicles where the driving tasks are performed by electronics and machinery instead of human driver. The vehicle is capable of sensing its environment and moving with little or no human input. The automated system has control over the vehicle but allows the human operator to leave all responsibilities to the system [Ref 30].
Keywords: Other cross-cutting concepts.

Automation pyramid: General design pattern for creating information and communication infrastructures (ICT) for industry [Ref 31].
Keywords: Other cross-cutting concepts.

Autonomic computing: The ability of IT infrastructures to adapt to change in a complex environment in accordance with business policies and objectives [Ref 32].
Keywords: Other cross-cutting concepts.

Autonomous Driving Levels: Automated driving systems are classified depending on their automation levels. These are going from 0 (no automation) where the driver performs all the driving tasks, up to 5 (full automation) where the vehicle is capable of performing all driving functions under all conditions [Ref 33].
Keywords: Automated driving systems, Other cross-cutting concepts.

Autonomous farming: The increasing maturity of digital and automation technologies is driving an increased offer in autonomous farming machinery. Autonomous farming machinery is able to operate without direct intervention of humans thanks to a combination of technologies such as geolocation, auto-steering, computer vision, Internet of things, sensing and Data Analytics, among others [Ref 34].
Keywords: Collaboration and Process Layer, farming.

Autonomy: The ability to generate one’s own purposes without any instruction from outside [Ref 35].
Keywords: Other cross-cutting concepts.

Availability: (i) General: Characteristic of a resource that is committable, operable, or usable on demand to perform its designated or required function. It is the aggregate of the resource's accessibility, reliability, maintainability, serviceability, and securability. (ii) Computing: Percentage of time a computer system is available for use. Formula: Uptime x 100 ÷ (Uptime + Downtime). (iii) Quality control: Ability of an item to perform its designated function, whenever required [Ref 36].
Keywords: Other cross-cutting concepts.


B


Barcodes: A barcode is an optical and machine-readable form of data used to identify objects. A bar Code allows a machine to retrieve a great deal of information about an object as soon as the object is identified through a unique visual code format created by drawing adjacent lines with variable widths and spaces [Ref 37].
Keywords: physical layer.

Benchmarking: Benchmarking is a process by which internal processes and performances are compared directly with recognised best practices as an external standard for comparison and goal setting that promotes learning from others [Ref 38].
Keywords: Other cross-cutting concepts.

Big data : Big data is a term referring to high volume information (data) assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation [Ref 39].
Keywords: Other cross-cutting concepts.

Big Data Value Association (BDVA): BDVA is an industry-driven international not–for-profit organisation with 200 European members (large, small, and medium sized industries as well as research and user organizations). BDVA is the private counterpart to the EU Commission to implement the Big Data Value PPP program. BDVA and the Big Data Value PPP pursue a common shared vision of positioning Europe as the world leader in the creation of Big Data Value. The mission of the BDVA is to develop the Innovation Ecosystem that will enable the data and AI-driven digital transformation in Europe [Ref 40].
Keywords: Other cross-cutting concepts.

Biodiversity: The variability among living organisms from all sources, including terrestrial, marine, and other aquatic ecosystems and the ecological complexes of which they are part. It includes diversity within species (genetic diversity), between species (species diversity), and between ecosystems (ecosystem diversity) [Ref 11].

Biofuel: This is a fuel (biodiesel, bioethanol, biomethane) that is produced by a biological process (as opposed to a geological process). Biofuels can be in a solid, liquid or gaseous form [Ref 11].

Biosensors: A biosensor is an analytical device, used for the detection of a chemical substance, that combines a biological component with a physicochemical detector [Ref 41].
Keywords: Other cross-cutting concepts.

Blockchain: Blockchain is an architectural design and a type of distributed ledger for maintaining a permanent and tamper-proof record of transactional data. A blockchain act as a decentralized database that is managed by computers belonging to a peer-to-peer network. Each of the computers in the distributed network maintains a copy of the ledger to prevent a single point of failure and all copies are updated and validated simultaneously [Ref 42].
Keywords: Security, Other cross-cutting concepts.

Blue economy: The Blue Economy acknowledges that some aspects of so-called "green living", such as buying organic food and using certain forms of renewable energy, can be economically out of reach for large sections of the population [Ref 43].
Keywords: Other cross-cutting concepts.

Broadband: It is a high-data-rate connection to the Internet [Ref 44].
Keywords: Other cross-cutting concepts.

Business ecosystem: An economic community supported by a foundation of interacting organizations and individuals. This economic community produces goods and services of value to customers, who are themselves members of the ecosystem. The member organisms also include suppliers, lead producers, competitors, and other stakeholders [Ref 45].
Keywords: Other cross-cutting concepts.

Business models: A business model is the ‘description of the rationale of how an organisation creates, delivers and captures value’, it is in its essence how a business generates (or plans to generate) a revenue stream that supports the delivery of a value proposition to a client segment [Ref 46].
Keywords: Other cross-cutting concepts.

Business-to-Business (B2B) model: The Business-to-Business (B2B) model refers to the exchange of products, services or information between businesses [Ref 47].
Keywords: Other cross-cutting concepts.

Business-to-Business-to-Consumer (B2B2C) model: The Business-to-Business-to-Consumer (B2B2C) model extends the B2B model to include e-commerce for the consumers (B2C) [Ref 48].
Keywords: Other cross-cutting concepts.

Business-to-Consumer (B2C) model: The Business-to-Consumer (B2C) model refers to the transactions conducted directly between a company and consumers (end-users of products/services) [Ref 49].
Keywords: Other cross-cutting concepts.


C


Cellular V2X (C-V2X: C-V2X is specified by 3GPP and is realized as LTE-V2X (3GPP rel. 14/15) for short- and long-range communication. The short-range mode works independently of cellular networks, supports V2V, V2I and V2P communication, uses direct side-link communication over PC5 interface, uses orthogonal frequency-division multiplexing (OFDM) in the 5.9GHz frequency band, and its MAC layer is based on semi-persistent scheduling allowing deterministic sharing of the medium among multiple stations in a distributed manner. While the long-range mode is cellular mobile network dependent and supports V2N communication, i.e. up/down link communication between vehicles and base stations in a cellular LTE network over Uu interface. The next release 5G NR-V2X (5G New Radio V2X, rel. 16) address improvements such as lower latency, increased reliable communication and higher data rates to support autonomous driving. 5G NR-V2X will complement LTE-V2X, i.e. not replace but co-exist with LTE-V2X [Ref 50].
Keywords: Other cross-cutting concepts.

Certification: Third-party attestation related to products, processes, systems or persons. Note that certification is applicable to all objects of conformity assessment except for conformity assessment bodies themselves, to which accreditation is applicable [Ref 51].
Keywords: Other cross-cutting concepts.

Circular Economy: An economic model based inter alia on sharing, leasing, reuse, repair, refurbishment and recycling, in an (almost) closed loop, aiming to retain the highest utility and value of products, components and materials at all times, i.e. a model in which waste is seen as a resource and is managed by design [Ref 52].
Keywords: Other cross-cutting concepts.

Citizen Centric: An adjective applied to e-Government services enabled by information and communication technology that fosters information integration across departmental lines, governmental units, and multi-sector organizations. These services, instead of forcing the user to understand their internal organization and adapt to them, respond to users' needs and behaviours even connecting various departments and increasing both their efficiency and effectiveness [Ref 53].
Keywords: Other cross-cutting concepts.

Cloud Computing: The term Cloud refers to networks hosting an often-large number of users through remote connection enabling a centralized storage of data and collaborative work. They can be categorized into Public (public spaces for users on which companies provide quick access), Private (owned and operated by single companies/users for their particular purposes) and Hybrid (combining a private foundation but also providing public access). Cloud computing involves delivering all kinds of data, applications, multimedia, etc. over the internet through different models of use, namely software as a Service SaaS, where companies offer cloud-based applications able to be connected through users), Infrastructure as a Service IaaS, on which remote online servers, networking and Data centres can be used by customers) and Platform as a Service (PaaS, combining both and, thus, eliminating the need to purchase and maintain hardware, software and hosting). Cloud computing tightly relates to IoT as the straightforward way to direct the huge amount of data collected by sensors/field devices to its destination [Ref 54][Ref 55][Ref 56].
Keywords: Service layer.

Co-creation: Value co-creation in IoT platforms ecosystems is addressing activities where customers, end-users, application owners and developers are involved as active participants in the design and development of personalized IoT applications, use cases, products, services, and experiences in IoT-platform ecosystems. In this context, the modernist dichotomy of producers as value creators and consumers as value destroyers is currently losing traction: Consumers – or prosumers – exert their power in the marketplace through constructive collective action with other societal actors such as developers, hackers, users, etc. beyond the providers’ control. This is common practice, for instance, in the world of Open Source software and hardware where collective effort, social interaction and group influence are all crucial to the development and use of products like Linux or Arduino. Moreover, co-creation in IoT doesn’t solely pertain to Human-centric design and design-thinking. Artistic thinking is also a key resource. Artists are facilitators of dialogue and are in a privileged position to empower and deepen IoT experiences. An example of a company facilitating co-creative practices in IoT is Little Bits, an open-source kit of electronic modules that snap together with magnets in a way to let anyone – children or rocket engineers – prototype or play [Ref 57][Ref 58][Ref 59].
Keywords: Other cross-cutting concepts.

Cognitive IoT (CIoT): In CIoT, cognitive computing technologies are included in the IoT network to add artificial intelligence and signal processing. Physical and virtual objects are interconnected and behave like "thinking agents" (machine learning, decision making) performing tasks with minimum human intervention. CIoT is particularly relevant to handle the big increase in IoT devices expected, and to utilize the huge amounts of data generated [Ref 60][Ref 61].
Keywords: Other cross-cutting concepts.

Collaboration: Enables AI-based IoT systems to self-organize around a common goal; for example, in the presence of a threat, as well as to collaborate with humans, both physically (e.g., human-robot collaboration) and by exchanging information (human-machine interfaces). Collaboration is an emergent property of complex interactions and dynamics, increasingly present in industry. Industry-grade AI will not be concentrated on a single device or system. Instead, many different AI-enabled subsystems will be distributed (distributed AI) across IoT nodes, embedded devices and other edge devices (embedded AI) [Ref 62].
Keywords: Other cross-cutting concepts.

Common Services Entity (CSE): A CSE represents an instantiation of a set of "common service functions" of the M2M environments. Such service functions are exposed to other entities through the Mca and Mcc reference points. Reference point Mcn is used for accessing underlying NSE. Each CSE is identified with a unique CSE-ID [Ref 63].
Keywords: Service layer, Other cross-cutting concepts.

Computer security incident response team (CSIRT): CSIRT is an expert group handling computer security. They receive reports of security breaches, conducts analyses of the reports and responds to the senders. A CSIRT may be an established group or an ad hoc assembly [Ref 64].
Keywords: Security,Other cross-cutting concepts.

Conditional automation: The driving-mode specific performance by an automated driving system of all aspects of the dynamic driving task with the expectation that the human driver will respond appropriately to a request to intervene[Ref 65].
Keywords: Other cross-cutting concepts.

Confidentiality: A set functionality that limits access or places restrictions on certain types of information, with the goal of preventing unauthorized access. Confidentiality is usually achieved through encryption and crypto- graphic mechanisms and is essential within an IoT ecosystem where a large amount of information is exchanged among the nodes[Ref 66].
Keywords: AI, IoT, Other cross-cutting concepts

Connected Supply Chain: Supply Chain management is defined as the integration of key business processes from the end-user through to original suppliers that provide products, services, and information and hence add value for customers and other stakeholders. In the context of IoT, a Connected Supply Chain is one that takes advantage of Information Technologies to integrate suppliers/partnering firms in virtual enterprise and supply chain [Ref 67].
Keywords: Application Layer.

Connectivity: The ability of a computer, program, device, or system to connect with one or more others [Ref 68].
Keywords: Network communication layer.

Consent: ‘Consent’ of the data subject means any freely given, specific, informed and unambiguous indication of the data subject’s wishes by which he or she, by a statement or by a clear affirmative action, signifies agreement to the processing of personal data relating to him or her [Ref 69].
Keywords: Other cross-cutting concepts.

Consumer awareness: The understanding by an individual of their rights as a consumer concerning available products and services being marketed and sold. The concept involves four categories: safety, choice, information, and the right to be heard [Ref 70].
Keywords: Other cross-cutting concepts.

Context-aware computing: Computer operations in which collect and analyse situational and environmental information about user activities, places and things are used to anticipate immediate needs and proactively offer enriched, situation-aware and usable content, functions and experiences [Ref 71].
Keywords: Other cross-cutting concepts.

Context-awareness: The ability of a system or a system component (e.g. mobile devices) to collect information about its environment at any given time and adapt behaviours accordingly [Ref 72].
Keywords: Other cross-cutting concepts.

Controller: ‘Controller’ means the natural or legal person, public authority, agency or other body which, alone or jointly with others, determines the purposes and means of the processing of personal data; where the purposes and means of such processing are determined by Union or Member State law, the controller or the specific criteria for its nomination may be provided for by Union or Member State law [Ref 73].
Keywords: Other cross-cutting concepts.

COP: COP (Common Operational Picture) is a component that provides an API that describes the current state of large open air events, i.e. active alerts, people count, sound level etc.
Keywords: Other cross-cutting concepts.

Core Network: The part of the network that provides services to mobile subscribers through the radio access network (RAN). It is also the gateway to other networks, for instance to the public- switched telephone network or to public clouds.

Corrective Maintenance: Also called run-to-failure reactive maintenance, corrective maintenance is the simplest maintenance policy where machine interventions (repairs) are only performed when a failure in operation occurs [Ref 23].
Keywords: Other cross-cutting concepts, Industry.

CPS: Cyber-Physical Systems (CPS) are integrations of computation, networking, and physical processes [Ref 74].
Keywords: Abstraction Layer

Creation: Creation is the action or process of bringing something into existence. Creation often describes the act of producing something for the first time and is, in this connotation, often linked to artistic creation. Artistic creation can bring resourceful insights in the process of building lively, user-centred and trustworthy IoT systems for broader adoption. David Bohm (1927-1992) advocated for dialogue among disciplines as the core of creativity. The arts are more about creation than creativity. However, artists can play a crucial role as catalysts of innovation in IoT by enabling an open dialogue with society in general and thereby fostering its process of uptake. Results of art and technology research projects are in their majority intend to take the form of proof of concept – they are creations. Knowledge is materialized in concrete applications which, very often, including usability testing in their early stages. This is one of the reasons why many artists have been at the origin of new technologies. The example of the Berlin-based company ART+COM is key. The company created the Terravision system in 1994 that many consider to be the prequel to Google Earth. It can be said that the artistic origin of one of the most successful worldwide on-line platforms lies in Europe, but was commercially explored elsewhere. More recently, Eduardo Miranda has developed the new bio- musical computer which potential s will certainly take some time to be unveiled [Ref 59][Ref 26].
Keywords: Other cross-cutting concepts.

Critical approach to IoT: To think out-of-the-box is a well-known objective in innovation processes. Artists, however, are more interested in getting rid of the box. It is this disruptive approach that is seen as fundamental to create a critical approach to technological developments. In this context, the integration of artists in technological research processes can be instrumental for the attribution of meaning to new technologies. A solid critical approach is fundamental for competitiveness based on knowledge and creativity. The critical approach is one of the main differential elements between artists and designers. An artist involved in a technological challenge would go deeper in the analysis of the challenge, with a critical eye. On the other hand, a designer would be driven by finding a solution - problem solving. An example of artistic critical approach in IoT is the work of artist James Brindle who is trying to build his own self-driving car and has published all the code developed in pursuit of the DIY self-driving car via this link https://github.com/stml/austeer. Brindle says “Self-driving cars bring together a bunch of really interesting technologies - such as machine vision and intelligence - with crucial social issues such as the atomization and changing nature of labour, the shift of power to corporate elites and Silicon Valley, and the quasi-religious faith in computation as the only framework for the production of truth - and hence, ethics and social justice. The attempt to build my own car is a process of understanding how the dominant narratives of these technologies are produced, and could be changed” [Ref 75][Ref 26][Ref 76].
Keywords: Other cross-cutting concepts

Cross-domain indicators: Indicators intercepting those processes and features pertaining to more than one domain potentially referring to more than one LSP but not to the IoT Programme as a whole [Ref 77].
Keywords: Other cross-cutting concepts.

Cryptography: Discipline that embodies principles, means, and mechanisms for the transformation of data in order to hide its information content, prevent its undetected modification and/or prevent its unauthorized use [Ref 78].
Keywords: Other cross-cutting concepts.

Cyber physical systems: Cyber-physical systems are combinations of intelligent physical components, objects and systems with embedded computing and storage possibilities, which get connected through networks and are the enablers of the smart factory concept of industry 4.0 in the scope of the Internet of things, data and Services scope, with a focus on processes [Ref 79].
Keywords: Other cross-cutting concepts.


D-F

D


DANTE (Digital Audio Network Through Ethernet) protocol: DANTE is a combination of software, hardware, and network protocols that deliver uncompressed, multi-channel, low-latency digital audio over a standard Ethernet network using Layer 3 IP packets [Ref 80].
Keywords: Protocol.

Data access: Ability to make use of the data in an information system resource. Data access refers to a user's ability to access or retrieve data] stored within a data base or other repository. Users who have data access can store, retrieve, move or manipulate stored data, which can be stored on a wide range of hard drives and external devices[Ref 81].
Keywords: Other cross-cutting concepts.

Data accountability: Accountability for data and its use
Keywords: Other cross-cutting concepts.

Data Analytics: Data Analytics comprises the needed operations needed to be performed so as to extract valuable information out of data, including discovery, interpretation and modelling. It makes full use of mathematical/statistical algorithms combined with performance and programming techniques. Data Analytics is often tied to Big Data. In this respect, IoT is a key enabler for Data Analytics, as IoT devices produce huge amounts of information that can susceptible to be used to generate models, studying patterns, feed intelligent decision systems and more, etc.[Ref 82][Ref 83].
Keywords: |Abstraction Layer, data, Analytics.

Data authentication: A process used to verify data integrity[Ref 84].
Keywords: Other cross-cutting concepts.

Data granularity: Degree of precision of data[Ref 85].
Keywords: Other cross-cutting concepts.

Data governance: The exercise of decision-making and authority for data-related matters. The organizational bodies, rules, decision rights, and accountabilities of people and information systems as they perform information-related processes [Ref 86].
Keywords: Data, Other cross-cutting concepts.

Data governance framework: The process of building a model for managing enterprise data. The framework or system sets the guidelines and rules of engagement for business and management activities, especially those that deal with or result in the creation and manipulation of data [Ref 87].
Keywords: Data, Other cross-cutting concepts.

Data integrity: The property that the data has not been altered or destroyed in an unauthorized manner.
Keywords: Other cross-cutting concepts.

Data minimization: The minimum necessary to collect, use, access, or disclose of data to avoid data breach and protect data for appropriate use.
Keywords: Other cross-cutting concepts.

Data ownership: Under EU law, personal data can only be gathered legally under strict conditions and, for a legitimate purpose. Furthermore, persons or organisations that collect and manage your personal information must protect it from misuse and must respect certain rights of the data owners which are guaranteed by EU law[Ref 88].
Keywords: Other cross-cutting concepts.

Data privacy:Rights and obligation of individuals and organizations with respect to collection, use, retention, disclosure, and disposal of personal information[Ref 89].
Keywords: Other cross-cutting concepts.

Data providers: These are companies and organisations that provide free and/ or paid data sources. It can include social networks, public administrations or private businesses that provide access to some of their own data. These players do not necessarily send their data; they can simply make them available through APIs [Ref 90].
Keywords: Other cross-cutting concepts.

Data protection: Under EU law, personal data can only be gathered legally under strict conditions, for a legitimate purpose. Furthermore, persons or organisations which collect and manage your personal information must protect it from misuse and must respect certain rights of the data owners which are guaranteed by EU law [Ref 91].
Keywords: Other cross-cutting concepts.

Data security: Data security refers to the protection of information by using appropriate technical measures that shall be taken against unauthorised or unlawful access or processing, and against accidental loss, destruction, or damage[Ref 92].
Keywords: Other cross-cutting concepts.

Data-Driven farming: The use of Big Data and contextual analysis to support decision making with the aim of reaching increasing productivity and profitability through precision agriculture.Keywords: Other cross-cutting concepts, Application Layer, Physical layer, Processing layer.

Decision (in SDL): An action within a transition which asks a question to which the answer can be obtained at that instant and, based on the answer selects one of the outgoing transitions from the decision to continue interpretation.[Ref 93].
Keywords: Other cross-cutting concepts.

Decision Support System (DSS): A computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization (usually mid- or/and upper management) and help people make decisions about problems that may be rapidly changing and not easily specified in advance, i.e. unstructured and semi-structured decision problems. Decision support systems can be either fully computerized, human-powered or a combination of both. [Ref 94].
Keywords: Application Layer.

Deep learning: Deep learning mimics human neural pathways to analyse unstructured data, providing multiple outputs/decisions through layered abstraction and pattern recognition [Ref 95].
Keywords: Abstraction Layer, Application Layer, Processing layer

DEI: See Digitising European.

Demand-driven farming: A farming operation that is driven by the demand that the farm experiences (or foresees) from successive stages in the supply chain (food processors, businesses, consumers). Demand-driven farming is facilitated by the combination of technologies such as IoT or (predictive) Data Analytics.[Ref 23].
Keywords: ProcessorsApplication Layer, Farming.

Device: Mechanical, electrical, or electronic contrivance with a specific purpose.[Ref 96].
Keywords: Application Layer,physical layer.

Device management: Device management refers to the process of monitoring the implementation, operation and maintenance of physical or virtual devices. IoT device management implies a set of operations including provisioning and Authentication, configuration and control, monitoring and diagnosis, software updates and maintenance[Ref 97].
Keywords: Application Layer, Security.

Digital: Digital describes electronic technology that generates, stores, and processes data in terms of two states: positive and non-positive [Ref 98].
Keywords: Processing layer.

Digital assistants: Applications that perform digital tasks for the user using speech recognition and natural language processing, e.g. Siri, Alexis.Keywords: Service layer, Application Layer, Processing layer.

Digital Automation: See Smart Manufacturing.

Digital connection: An association of digital circuits, digital switches and other functional units providing means for the transfer of digitally encoded information signals between two terminal points.[Ref 99].
Keywords: Other cross-cutting concepts.

Digital economy: The sum of all economic activity that relies upon or produces internet-enabled technologies like e-commerce, cloud computing, artificial intelligence and the Internet of things [Ref 100].
Keywords: Collaboration and Process Layer.

Digital Industrial Platforms: A Digital Industrial Platform integrates (data from) various functions implemented by different technologies via clearly specified interfaces and makes data available for use by applications. Digital Industrial Platforms bring together different technologies, applications and services. They open up data from e.g. the machines, products and operators on a shop floor, make it accessible to e.g. monitoring and control applications, may provide open interfaces that allow third-parties to develop applications on top, and connect different stakeholders, such as users and application developers [Ref 101].
Keywords: 'Abstraction Layer'

Digital innovation: Digital innovation is the application of new technologies to existing business problems or practices. The unique properties of digital technology enable new types of innovation processes that are distinctly different from the analogue innovation processes of the Industrial Era [Ref 102].
Keywords: Other cross-cutting concepts.

Digital Manufacturing: See Smart Manufacturing

Digital Platforms: Digital platforms are the base upon which an increasing number of connection-based activities – marketplace, social, and political - are being organized. If the Industrial revolution was organized around the factory, today’s changes are organized around platforms and algorithms applied to enormous databases running in the Cloud [Ref 103].
Keywords: Other cross-cutting concepts.

Digital Rights Management: Digital rights management (DRM) is access-control technology used by manufacturers, publishers, and copyright holders to limit the use of digital devices or information. It describes the technology that prevents unauthorized distribution and use of content, media, or device[Ref 104].
Keywords: Other cross-cutting concepts.

Digital service provider (DSP): Digital service providers (DSPs) are online marketplaces (which allow businesses to set up shops on the marketplace in order to make their products and services available online), Cloud computing services, and search engines.
Keywords: Other cross-cutting concepts.

Digital Single Market: A Digital Single Market is one in which the free movement of persons, services and capital is ensured and where the individuals and businesses can seamlessly access and exercise online activities under conditions of fair competition, and a high level of consumer and personal data protection, irrespective of their nationality or place of residence [Ref 105].
Keywords: Other cross-cutting concepts.

Digital Twins: Digital twins are virtual representations of material assets. For the IoT, digital twins have never been trendier, as IoT vendors are using increasingly more advanced technology for their implementation, not least with an add-on marketing effect. The digital twin, as a virtual representation of the IoT’s physical object or system across its lifecycle, using real-time data to enable understanding, learning and reasoning, is a one element connecting the IoT and AI. The digital twin represents the virtual replica of the IoT physical device by acting like the real thing, which helps in detecting possible issues, testing new settings, simulating all kinds of scenarios, analysing different operational and behavioural scenarios and simulating various situations in a virtual or digital environment, while knowing that what is performed with that digital twin could also happen when it is done by the ‘real’ physical “thing”. Digital twins as part of IoT technologies and applications are being expanded to more applications, use cases and industries, as well as combined with more technologies, such as speech capabilities, AR for an immersive experience and AI capabilities, enabling us to look inside the digital twin by removing the need to go and check the ‘real’ thing.[Ref 106].
Keywords: AI,IoT,Other cross-cutting concepts

Digitising European Industry (DEI): The DEI Strategy was launched in April 2016 by the European Commission as an articulated set of measures to help European industry, SMEs, researchers and public authorities make the most of digital technologies such as IoT[Ref 107].
Keywords: Other cross-cutting concepts, Industry, Policy.

Directive on security of network and information systems (NIS Directive): The NIS Directive is the first piece of EU-wide legislation on Cybersecurity. It provides legal measures to boost the overall level of cybersecurity in the EU. The NIS Directive was adopted by the European Parliament in July 2016 and entered into force in August 2016. Member States must transpose the Directive into their national laws by May 2018 and identify operators of essential services by November 2018.[Ref 108].
Keywords: Legislation,Other cross-cutting concepts.

Domain-specific indicators: Indicators designed for, and applying to, a single domain used to measure the performance and impacts of one specific LSP[Ref 109].
Keywords: Other cross-cutting concepts.

DSM: See Digital Single Market


E


Edge computing:Edge computing is a way to optimize Cloud computing systems by using edge device computational capabilities to run analytic/knowledge generation functions and, thus, reducing the processes performed on the Cloud. Locating this data processing near the data sources also allows a reduction of the bandwidth as only relevant aggregated information is transferred. The application of edge computing to IoT might be the solution to the current concern about not having enough resources at Cloud level to process the overall data being reported by IoT devices. Nevertheless, there are some barriers to overcome to reach a truly functional IoT edge computing network, such as the potential unavailability of devices due to its often used wireless link or the scheduling/coordination problems that may arise when deploying it at large scale[Ref 110].
Keywords: network communication layer, Wireless.

Edge device/node: Hardware or physical component. In IoT, usually the hardware acting a bridge between sensors and internet. It is also capable of covering computing capabilities not supported by sensors
Keywords: Other cross-cutting concepts.

Electronic commerce (e-commerce): Electronic commerce (e-commerce) refers to business transactions of goods and services, or the transmitting of funds or data, over internet. These transactions occur either as B2B, B2C/C2B, or C2C.[Ref 111].
Keywords: Other cross-cutting concepts.

Electronic labelling (e-labelling): e-labelling is an alternative for manufacturers for indicating compliance information. This can be done electronically through embedding it in the software of devices with a built-in screen, connection to a screen, or through machine readable-codes (e.g. QR-codes). ECSO WG1 is working on labelling together with standardisation, certification, and supply chain management, developing a roadmap for the development of security standards and certification. For Cybersecurity e-labelling, there is a trade-off between the simplicity required for the understanding by a non-expert consumer, and the information presented in the cybersecurity label[Ref 112].
Keywords: Other cross-cutting concepts,Security.

Embedded systems: Embedded systems are dedicated mini-computers serving as parts of a larger mechanical, electrical or communications system. They often suffer from real-time and/or computing capabilities constraints. These systems include hardware and mechanical parts and are commonly used as monitoring and control devices for a plethora of applications. IoT disrupted the way embedded systems were traditionally conceived as they require very strict miniaturization, communication and processing capabilities. This disruption touches upon not just hardware design for embedded systems, but also software programming models and Operating System design [Ref 113][Ref 114].
Keywords: Physical layer.

Enabling network: The organization of communication between various devices in applications such as smart grids, smart meters, smart houses, smart healthcare systems, smart industries, etc.[Ref 115].
Keywords: 'Network communication layer'

End-nodes: The bottom layer in an IoT Platform or architecture. Physical components capable of collecting data, sensing and acting.
Keywords: Other cross-cutting concepts.

End-to-end security: (i) Safeguarding information in a secure telecommunication system by cryptographic or protected distribution system means from point of origin to point of destination. (ii) Safeguarding information in an information system from point of origin to point of destination[Ref 116].
Keywords: Other cross-cutting concepts, [[#Security|Security].

End-user: A human being, organization, or telecommunications system that accesses the network in order to communicate via the services provided by the network.[Ref 117].
Keywords: Application Layer,Other cross-cutting concepts.

Energy crops: These are crops which are grown for energy, rather than for food or fibre. They include oilseeds crops (e.g. oilseed rape, soya, sunflower), cereals (e.g. wheat, barley, maize, rye), sugar beet, sugarcane and perennial crops (e.g. miscanthus, short rotation coppice, eucalyptus) [Ref 11].

Enhanced mobile broadband (eMBB): Enhanced Mobile Broadband (eMBB) is one of three sets of use cases defined by 3GPP for 5G, (data-driven use cases requiring high data rates across a wide coverage area). For other sets of use cases, see uRLLC and mMTC.[Ref 118].
Keywords: Wireless, Other cross-cutting concepts.

Ethics: Ethics refers to universally- or socially-accepted norms and behaviours. Ethics are concerned with what is good for the individual and society and the associated behaviours and actions[Ref 119].
Keywords: Other cross-cutting concepts

European Agricultural Fund for Rural Development (EAFRD):This fund was created in September 2005 and came into operation at the beginning of 2007. It replaced the guarantee section of the European Agricultural Guidance and Guarantee Fund. It provides funding for direct payment to farmers, for the management of the agricultural markets and for a number of other purposes such as veterinary and plant health measures, food programmes and information activities [Ref 11].

European Cyber Security Organisation (ECSO):ECSO is the industry-led contractual counterpart to the European Commission (EC) for the implementation of the Cyber Security contractual Public-Private Partnership (cPPP). ECSO members include a wide variety of stakeholders and is instrumental in providing support to the EC for a new certification scheme. The main objective is to support all types of initiatives and projects that aim to develop, promote, encourage European cyber security. Particularly aims to foster and protect from cyber threats the growth of the European Digital Single Market (DSM)[Ref 120].
Keywords: Other cross-cutting concepts

European Network for Rural Development (ENRD):The European Network for Rural Development was established in 2008 by the European Commission to help member states implement their Rural Development programmes in an efficient manner. The network provides a forum for connecting rural Europe. It also serves as a platform for sharing ideas and experiences as to how Rural Development programmes work in practice and how they can be improved. Its main stakeholders include national rural networks, member state authorities, local action groups and other Rural Development organisations having an EU perspective. The network shares information with stakeholders in a variety of ways, including through its publications and its participation in events and fairs across Europe.[Ref 11]

European Platforms Initiative (EPI): See IoT European Platforms Initiative.

European Research Cluster on the Internet of Things (IERC): IERC is coordinating and building a broadly-based consensus on the ways to realise the Internet of Things vision in Europe. Their objectives are to identify IoT technology research challenges at the European level in the view of a global development. The IERC cluster brings together several members from through IoT projects within EU and aim to address the large potential for IoT-based capabilities in Europe and to coordinate the convergence of ongoing activities.[Ref 121].
Keywords: Other cross-cutting concepts

European Union Agency for Network and Information Security (ENISA):ENISA is a centre of expertise for cyber security in Europe (located in Greece), and is actively contributing to a high level of network and information security (NIS) within the Union. The agency works closely together with the Members States and private sector to deliver advice and solutions. and to raise the awareness of NIS.[Ref 122].
Keywords: Other cross-cutting concepts

Evolved 4G eNB (eLTE eNB):An eLTE eNB can support connectivity to the 4G evolved packet core (EPC) as well as the 5G next- generation core network (NGC or NGCN).

Evolved Node B (eNB or eNodeB):The part of the cell tower as defined by 4G LTE to be used within the base station that provides radio access to the user equipment (UE).

Experience Readiness Level: The Experience Readiness Level (ERL) measures the capability of IoT systems to trigger experiences, a measure that steps away from the modernist ideal of the «perfect object» and embraces the potential of a thriving, dynamic exchange between technology and art to empower the spectator and deepen his or her experience. The ERL is a complimentary approach to Technology Readiness Level (TRL), Market Readiness Level (MRL) and Production Readiness Level (PRL). Kevin Ashton in 1999 coined the term IoT, and understood it as an evolution of the Internet whereby "we empower computers with their own means of gathering information, so they can see, hear and smell the world for themselves, in all its random glory". Nowadays, we understand the power of the hyper-connected society is about empowering citizens, not computers. A shift of attention from labs and drawing boards to involving existing and new communities at an early stage of IoT development is fostered and advocated. If the goal is the adoption of IoT by masses in full confidence, it's important we stop thinking about IoT as objects and start thinking of IoT as triggers for better lives. The Experience Readiness Level (ERL) is a new notion that introduces the focus on 'better lives' and moves the attention from the production to the consumption of IoT[Ref 123][Ref 124].
Keywords: Other cross-cutting concepts.

Explainability: Enables human users to understand the decisions made by AI systems and the rationale behind them. This ability will make it easier to track down eventual failures and assess decisions’ strengths and weaknesses. Ultimately, this will increase the trust in the systems’ decisions. This ability will have to integrate with human-computer interface techniques which are able to track complex reasoning processes[Ref 125].
Keywords: AI, IoT, Other cross-cutting concepts


F


Factories of the futures (FoF): The FoF is a Public-Private Partnership (PPP) initiative for helping EU manufacturing enterprises (in particular SMEs) to adapt global competitive pressures by developing the necessary key enabling technologies across a broad range of sectors. It will help European industry to meet increasing global consumer demand for greener, more customised and higher quality products [Ref 126].
Keywords: Other cross-cutting concepts.

Fairness: Enables IoT systems which embed AI technologies to support or automate decision processes while adhering to the same fairness and compliance standards as humans [Ref 127].
Keywords: AI,IoT,Other cross-cutting concepts

Farm Accountancy Data Network (FADN): The farm accountancy data network provides data on the financial and economic aspects of various types of farming in the member states of the European Union. Each year a sample of farms is selected which is representative of commercial farms. These farms provide data on their costs of production, their revenues from sales and other aspects of their farming operations. The data enable the European Union to monitor the income situation of farmers and to examine the effects of the Common Agricultural Policy [Ref 11].

Farmer: In the context of the Common Agricultural Policy, a farmer is an individual (or group of individuals e.g. partnerships, companies, and other legal structures through which a business is conducted) whose holding is situated with the territory of the European Union and who exercises an agricultural activity [Ref 11].

Farming: The activity or business of raising crops or livestock [Ref 128].
Keywords: Other cross-cutting concepts.

Federation of platforms: An approach to enterprise architecture that allows interoperability and information-sharing between semi-autonomous business units [Ref 129].
Keywords: Collaboration and Process Layer.

Fog computing: Fog computing refers to a mechanism similar to edge computing, but using one or more end devices acting as gateways/data-processing units performing substantial storage, control, configuration, measurement and management activities for a given number of associated end devices and, therefore, reducing the Cloud processing needs [Ref 130].
Keywords: Network communication layer.

Food Safety: This term refers to the extent to which food is safe to eat. The term is sometimes confused with food security which refers to the extent to which food is available - i.e. whether it is physically available and can be bought at a price that people can afford [Ref 11].

Food Security: Food security exists when all people, at all times, have physical and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life [Ref 131].
Keywords: Other cross-cutting concepts, Farming, Agrifood.

Food supply chains: The processes and participating organisations through which food reaches the consumer from the farm of origin, it includes farmers, processors, distributors, retailers and consumers [Ref 132].
Keywords: Processors,Other cross-cutting concepts.

Food Traceability: Ability to track any food, feed, food-producing animal or substance that will be used for consumption, through all stages of production, processing and distribution [Ref 133].
Keywords: Other cross-cutting concepts, Agrifood.

FROST: A Server implementation of the OGC. [Ref 134]

FTC: The Federal Trade Commission is an independent agency of the United States of America that has jurisdiction to enhance consumer welfare and protect competition in broad sectors of the economy [Ref 135].
Keywords: Other cross-cutting concepts.

Full automation: The driving mode specific performance by an automated driving system of all aspects the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver [Ref 136].
Keywords: Other cross-cutting concepts.

Functional Ink: Functional printing means the additive printing of electronic components and circuits on a carrier material such as paper or foil [Ref 137].
Keywords: Physical layer.


G-I

G


General Data Protection Regulation (GDPR): 'The General Data Protection Regulation (GDPR) is the Regulation (EU) 2016/679 to harmonize data privacy laws across Europe and ensure the protection of privacy regarding the processing and free movement of personal data. In particular, the individual's right to control their personal data and their right to protection of personal data. It applies to any organization, whether private or public, that processes personal data, and imposes the obligation to implement appropriate technical and organisational measures to ensure a level of security appropriate to the risk [Ref 138].
Keywords: Other cross-cutting concepts.

Generic indicators: 'Indicators referring to areas of performance or evaluations that are common to all KPIs and all products, services and projects [Ref 139].
Keywords: Other cross-cutting concepts.

Google Next: 'IoT ecosystem provided by google with different devices: thermostat, cameras, video doorbells, etc. Focused on smart homes. Everything managed and centralized with an special device called: Nest Hub[Ref 140]
Keywords: Other cross-cutting concepts.

GOST: Go implementation of OGC SensorThings API OGC. [Ref 141]

Governance: 'Governance' refers to the rules, processes and behaviour that affect the way in which powers are exercised, particularly in regard to openness, participation, accountability, effectiveness and coherence. IoT governance refers to the development and application by Governments, the private sector and civil society of shared principles, norms, rules, decision-making procedures, and programmes that shape the evolution and use of the Internet of things in a direction that addresses policy concerns and ensures that the maximum benefits are reaped[Ref 142]
Keywords: Other cross-cutting concepts.

GPU: 'Graphical Processing Unit. Mainly used for multimedia purposes: video, videogames, desktops acceleration, etc. Lately, used to support AI/ML high processing demands. It can be found in IoT Edge devices.[Ref 143]
Keywords: Other cross-cutting concepts,ML,AI.


H


H2M: See Human-to-Machine communication

High automation: The driving mode specific performance by an automated driving system of all aspects the dynamic driving task, even if a human driver does not respond appropriately to a request to intervene.[Ref 144].
Keywords: Other cross-cutting concepts.

High Performance Computing (HPC): HPC refers to the use of aggregated computing power for handling computation- and data-intensive tasks [Ref 145].
Keywords: Other cross-cutting concepts, Processing layer.

HMI: See Human-Machine Interfaces

Holistic innovation: Europe strongly relies on innovation to compete globally and to make human activities more sustainable and our society more inclusive. It is not about technology as such but about a better life for all of us. To achieve that, industry and technology have to think in a more holistic way to conceive radically novel products, services and processes that are also putting the human at the centre. Despite this imperative to work across boundaries and silos, Europe is still addressing innovation without fully engaging the creative forces that lie at the crossover of the arts – and, more generally, culture - science, and technology. In technology, Europe has historically focused its attention on R&D and standardization in technology. This led to initial successes e.g. in mobile telephony (Nokia and the GSM standard). Today, however, focusing only on technology is trapping us in incremental innovation. In a situation of saturated and over-engineered European economies, change is considered as being risky and innovation often remains bound to an already existing logic. Holistic innovation happens when one overcomes stereotypes on the technology and culture divide that are an impediment to engaging in Cross-Border R&I and to unleashing creative forces [Ref 146][Ref 147].
Keywords: Other cross-cutting concepts.

Home Automation: Home automation or domotics is building automation for a home. A home automation system will control lighting, climate, entertainment systems, and appliances. It may also include home security such as access control and alarm systems. When connected with the Internet, home devices are an important constituent of the Internet of Things [Ref 148].
Keywords: Application Layer,IoT

HPC: See High Performance Computing.

Human-centred IoT: It is commonly recognised that IoT has the potential to drastically improve our personal lives, our work places and our industrial / manufacturing efficiencies and capabilities. There is, however, a concern that IoT may lead to alienation because of objects capable of ‘talking’ to one other and to lose sight of humanpreferences. One of the main challenges for the implementation of IoT is to develop a Human-centred IoT, an ecosystem where citizens aren’t forced to compliance and data share data while losing sight of their agency capacity for agency, but can instead trust that the IoT systems around them operate according to understood principles and guarantees for their integrity, privacy and security whilst allowing room for fantasy and appropriation. A Human-centred IoT would imply an environment where IoT will empower people and not transform them into hostages of technology. Always being connected to the things around us has the potential to lead to more surveillance or more profiling by public authorities and private entities. More generally, without appropriate legal, technical and organisational safeguards, the IoT may facilitate the emergence of a de-humanised world, where machines enforce rules stringently, reduce humans’ freedom, and room for fantasy, and contact among them by make steps to controlling their behaviour. Director-General Roberto Viola also recently expressed this position: "The Next Generation Internet must be built for the humans respecting our European values" [Ref 149].
Keywords: Other cross-cutting concepts, Security.

Human-centred production: Human-centred production is an innovative technology that can efficiently utilize human and material resources in order to secure production locations.[Ref 150]
Keywords: Application Layer.

Human-Machine interface (HMI): The user interface of a mechanical system, a vehicle or an industrial installation [Ref 151].
Keywords: Application Layer.

Human-to-Machine (H2M) communication: H2M communication is an important development within IoT for applications like remote health monitoring and activity tracking. In vivo or in vitro devices (implantable, swallow able or wearable) collect sensor data and use a wireless interface for transmitting the data. The recipient could be the health care system (physician, nurse, etc.). See also Machine-to-Human (M2H) communication.
Keywords: Wireless, Other cross-cutting concepts.

Hybridity: Hybrid arts is a contemporary art movement in which artists work with frontier areas of science and emerging technologies. Artists work with fields such as biology, robotics, physical sciences, experimental interface technologies (such as speech, gesture, and face recognition), artificial intelligence, information visualization, and many others. They address the research in many ways such as undertaking new research agendas, visualizing results in new ways, or critiquing the social implications of the research. A ‘hybrid creative’ is a transdisciplinary practitioner owning specific technical skills that may enable one to expertly and fluently navigate the specifics of the fields or ICT as well as the arts. Hybridity of competences of practitioners allows a hybrid creative to simultaneously or alternately approach a circumstance in a problem-solving mode, design thinking, and/or in a critical approach mode, artistic thinking. [Ref 152][Ref 26].
Keywords: Other cross-cutting concepts.

Hyper-connected Society: A society where anyone and anything is connected regardless of time and place. All humans and physical objects do (or have the possibility to) communicate with each other through a communication network [Ref 153].
Keywords: Other cross-cutting concepts.

Hyperconnectivity: Hyperconnectivity means that anyone or anything is connected anytime and anywhere. All humans and physical objects should (or have the possibility to) communicate with each other through a communication network [Ref 153].
Keywords: Other cross-cutting concepts.


I


ICT Art Connect: ICT Art Connect is the name of a study of the European Commission that revealed new evidence for the integration of the Arts as an essential and fruitful component within research and innovation in ICT. ARTSHARE, along with imec, the coordinating organism of the Flemish Government for ICT research, carried out the study ICT ART CONNECT: Activities Linking ICT and Art: Past Experience - Future Activities, and created a map of institutions and individuals engaged in artistic practices within ICT research projects in Europe and worldwide. Because of the study, the European Commission launched the STARTS programme: innovation at the nexus of Science, Technology and the Arts. ICT Art Connect concept is no longer used in the European context and has been replaced by STARTS[Ref 26].
Keywords: Other cross-cutting concepts.

Identification: The act of allowing a device or service to be specifically and uniquely identified without ambiguity. This may take the form of RFID tag identifiers, IP addresses, global unique identifiers, functional or capability identifiers, or data source identifiers [Ref 154].
Keywords: AI,IoT,Other cross-cutting concepts

Identity and Access Management (IAM): IAM facilitates management through digital identities and is the security discipline that enables the right individuals to access the right resources at the right times for the right reasons. Mission-critical needs are addressed to ensure appropriate access to resources across increasingly heterogeneous technology environments, and to meet increasingly rigorous compliance requirements. ECSO have identified IAM as an area that will be challenged by IoT with its extended range of needs created by the increased mixture and scale and distribution of devices brought on by IoT, M2M and H2M interactions.[Ref 155].
Keywords: Security,Other cross-cutting concepts.

Impact Attainment Strategy (IAS) KPIs: KPIs that target both the technological evaluation of the IoT platform and the impact evaluation that focus on dissemination, standardization and co-creation KPIs.[Ref 156].
Keywords: Other cross-cutting concepts.

Inclusiveness: Enables AI-based IoT systems to allow human intervention even in the most automated decision and communication processes. This is essential to avoid the formation of isolated non-AI capable sub-systems within a process, production system or supply chain.[Ref 157].Network communication layer

Independent living: Independent living is the daily demonstration of human rights-based disability policies. Independent living is possible through the combination of various environmental and individual factors that allow disabled people to have control over their own lives. This includes the opportunity to make real choices and decisions regarding where to live, with whom to live and how to live. Services must be available, accessible to all and provided on the basis of equal opportunity, free and informed consent, and allowing disabled people flexibility in their daily lives. Independent living requires the built environment, transport and information to be accessible as well as the availability of technical aids, access to personal assistance and/or community-based services. It is necessary to point out that independent living is for all disabled persons, regardless of gender, age and the level of their support needs [Ref 158].
Keywords: AI,IoT,Other cross-cutting concepts

Industrial Internet of things (IIoT): The IIoT is a subset of the IoT, where edge devices, processing units and networks interact with their environments to generate data to improve processes. It also, and describes the IoT when used across various several types of industrial sectors, (manufacturing, logistics, energy, etc.)[Ref 159][Ref 160].
Keywords: Other cross-cutting concepts.

Industry 4.0: Industry 4.0 is the naming provided to the current automation trend for manufacturing in which cyber-physical systems, IoT and Cloud computing combine together. It is also referred to as smart manufacturing. It is the next expected industrial Revolution, preceded by the mechanization and steam power (1st Revolution, the electrical mass production assembly line (2nd Revolution and computer automation (3rd Revolution). In this complex new process, cyber-physical systems monitor real processes, creating a virtual copy of the real world and making decentralized decisions. IoT is used to permit communicate these cyber-physical systems to communicate with other systems and humans, in a way that they can jointly collaborate in real- time. All relevant data is centralized and exploited in Cloud computing services, optimizing the maintenance and decision taking procedures [Ref 161][Ref 162].
Keywords: Other cross-cutting concepts.

Information technology (IT): IT is the application of computers to store, operate, communicate, gather and manipulate information, in the business context. It is often regarded as a branch of Information and Control Technologies (ICT). It is often used as a synonym for computer networks, although it covers a wider spectrum of technologies, such as television and Cellular communications, among others, including IoT and wireless sensor devices, and others. Alternatively, a set of tools, processes, and methodologies and associated equipment employed to collect, process and present information [Ref 163].
Keywords: [#Wireless|wireless]], Other cross-cutting concepts, ICT.

Infrastructure: Infrastructure is the foundation or framework that supports a system or organization[Ref 164].
Keywords: 'Abstraction Layer'

Innovation: The traditional definition of innovation is the launch of a new product or version new species of an already known product, application of new methods of production or sales of a product (not yet proven in the industry), opening of a new market (the market for which a branch of the industry was not yet represented), acquiring of new sources of supply of raw material or semi-finished goods, or a new industry structure such as the creation or destruction of a monopoly position. A more up-to-date definition can refer to the successful implementation (as evidenced by the market introduction) of an idea that provides a novel solution to a problem [Ref 165].
Keywords: Other cross-cutting concepts.

Innovation Ecosystems: While a concrete definition has not been decided, we propose that an innovation ecosystem refers to the interdependent agencies and agents (e.g. universities, corporates, start-ups, public bodies) that drive the innovation process from conception to market which involving cooperation and competition [Ref 166].
Keywords: Other cross-cutting concepts.

Integrator: The integrators offer businesses the opportunity to build an application which meets their own needs and then integrate or install it on the server of the customer. These applications typically operate with multiple elements of a company IT system. For example, an application can automatically extract data from the customer database and subsequently analyse it with a big data integrated application
Keywords: Other cross-cutting concepts.

Integration: Enables IoT-embedding AI systems to exhibit an open and flexible perspective by consolidating insights from all existing systems and processes. Bridging possible gaps is a key prerequisite of the establishing AI methods in the industry according to a sustainable roadmap [Ref 167].
Keywords: AI, IoT, Other cross-cutting concepts

Integrity: A critical measure in information assurance and is defined as providing consistency or a lack of corruption within the IoT system. It requires the final information received to correspond with the original information sent and that data cannot be modified without detection. Malicious modification of the information exchanged may disrupt the correct functioning of an entire IoT ecosystem [Ref 168].
Keywords: AI,IoT,Other cross-cutting concepts

Intelligent Building Management System (IBMS): Intelligent building management systems (IBMS) are used to manage the technology involved in modern buildings. All the management systems installed in a building are integrated in the IBMS via an Internet protocol (IP) network, enabling the management of all the subsystems through a single front-end interface. This helps to reduce the energy consumption and carbon footprint of the building, to maintain its infrastructure, to comply with regulations, to reduce operating costs, to reduce the need for inspection, to reduce errors and failures, and to improve building safety, among others.[Ref 169].
Keywords: Application Layer.

Intelligent Vehicles: An intelligent vehicle is defined as a vehicle equipped with perception, reasoning, and actuating devices that enable the automation of driving tasks such as safe lane following, obstacle avoidance, overtaking slower traffic, following the vehicle ahead, anticipating and avoiding dangerous situations, and determining the route. The general motivation for the development of intelligent vehicles is safer, more convenient and efficient road traffic. [Ref 170].
Keywords: Other cross-cutting concepts.

Interface: An interface is a point of interaction between two systems.
Keywords: Other cross-cutting concepts.

Internet of Autonomous things (IoAT): IoAT refers to bring devices things, including artificial intelligence and machine learning, being brought into the physical environment as autonomous entities, moving and interacting with humans and other devices without human intervention. IoAT includes topics like mastering varied surroundings, device identification, dynamic discoverability, context- based cognitive network integration, and seamless platform integration. Examples of IoAT applications are autonomous vehicles and self-navigating drones. Sometimes the expression Autonomous Internet of things (A-IoT) is used for IoAT [Ref 159][Ref 171].
Keywords: Other cross-cutting concepts.

Internet of Buildings (IoB): An application domain of IoT, where information from multiple intelligent building management systems are gathered and integrated by IoB, for optimising the behaviour of individual buildings as part of a larger information system. The edge devices are important components for value creation through data collection, exchange and processing [Ref 159].
Keywords: Other cross-cutting concepts.

Internet of energy (IoE): A dynamic energy network infrastructure including energy cloud storage based on standard and interoperable communication protocols that interconnect the energy network with the Internet allowing units of energy (locally generated, stored, and forwarded) to be dispatched bidirectionally when and where it is needed. The related information/data and financial transactions follows the energy flows thus implementing the necessary information exchange together with the energyand financial transfers. Internet of Energy refers to the current trend among followed by energy producers and distribution grid operators of upgrading and automating electricity infrastructures to adapt the to the new decentralized and customer- centred model pushed by renewable energies, the new role of prosumers and the adoption of novel communication and data processing technologies. IoT plays a key role on this new Internet of Energy concept. IoT devices will be put in place on all value chain parts, including monitoring devices for energy plants (allowing optimal operation and maintenance for the generation), automating and controlling devices on the grid (smartening the distribution grid) and real-time monitoring on customer side (enabling real-time bi-directional communication with users) [Ref 14][Ref 172][Ref 173][Ref 174].
Keywords: Application Layer.

Internet of Health (IoH): An IoT application domain within the healthcare sector. The IoH concept refers to a large-scale system for reliable communication, information exchange and interaction possibilities facilitating more efficient, affordable and better-quality healthcare, together with enhanced patient experience and engagement. For instance, through improved or new remote health- monitoring and activity- tracking methods; diagnostics, treatment and medication methods; and patient flow, record-keep journaling and administrative methods. New communication, health and welfare technologies provide new services regardless of geographic localisation. A careful balance between data access and sharing of information are required to ensure security and privacy [Ref 23][Ref 175].
Keywords: Other cross-cutting concepts.

Internet of Mobile Things (IoMT): This is an application domain where mobile devices things are included in the IoT network/system. These mobile devices are characterized by increasing diversity and number, which challenge device identification, dynamic discoverability, context based cognitive network integration, and seamless platform integration. Some general examples of mobile devices today are sensors/actuators embedded in smartphones, smartwatches and cameras. To avoid misunderstandings, we mention that the abbreviation IoMT is also used for Internet of Medical things [Ref 159][Ref 176].
Keywords: Other cross-cutting concepts.

Internet of Robotic Things (IoRT): A concept that incorporate robotics aspects into the IoT landscape to provide advanced robotic capabilities, where intelligent devices (robotic things) are able to monitor events, collect sensor data from different sources, and use distributed intelligence to determine best solutions before effectuating an action on objects in the physical world. See also Robotic things[Ref 159][Ref 177][Ref 178].
Keywords: Other cross-cutting concepts.

Internet of Vehicles (IoV): The IoV concept refers to connected vehicles in a large-scale distributed system for reliable dynamic communication and information exchange facilitating smart mobility and transport, through traffic management, information services, environmental protection, road safety, assisted/autonomous driving, etc. The communication network includes both mobile internet communication, inter-vehicle/infrastructure communication, and intra-vehicle communication, as well as storage, artificial intelligence, learning, sensing, and decision-making capabilities [Ref 159][Ref 177][Ref 178].
Keywords: Other cross-cutting concepts.

Interoperability: Interoperability is a characteristic of a product or system, whose interfaces are perfectly able, to work with other products or systems, at present or future, in either implementation or access, without any restrictions[Ref 179].
Keywords: Other cross-cutting concepts.

IoB: See Internet of Buildings

IoE: See Internet of energy

IoH: See Internet of Health

IoRT: See Internet of Robotic things

IoT: See Internet of things

IoT Applications: Applications that run in an IoT system.

IoT Data: Data is the real value offered by IoT. Most business models for IoT are based on how to exploit and extract value out of the data being posted by deployed IoT devices in the field. In this data-driven scenario, it is critical to conduct measurements properly. The phenomenon/device monitored should be carefully selected to assure its relevance. Moreover, the accuracy of the measurement should also be guaranteed so as to avoid misleading information and, therefore, decisions. These decisions should drive data processing and Analytics. A business strategy for IoT should consider how to exploit data through analysis[Ref 180][Ref 181].
Keywords: Storage layer, data, Analytics.

IoT devices: IoT devices range from large, industrial sensing devices to tiny implants or from high-demanding video-surveillance devices to low-rate pulse sensors. They all have in common that they are deployed to serve a business/industry/particular need and are able to remotely report data. In terms of communication capabilities, they can use short-range radio interfaces (usually being grouped towards a high-end device acting as gateway to the Internet), long-range radio interfaces (such as LPWAN, Cellular, etc.) or even wired communication links. They can also be classified as just data-posting devices (unicast communication link) or actuators (accepting external commands and, thus, using bidirectional communication links) [Ref 180][Ref 181].
Keywords: Physical layer.

IoT Ecosystem: Solutions comprising large heterogeneous systems of systems, solving challenges across application verticals. In these ecosystems, IoT acts as an essential driver for optimization, innovation, competitiveness and business based on enabling technologies and collaboration among various stakeholders. It increases the value creation through exchange of information between multiple domains while maintaining privacy and security. Complementary architecture for seamless IoT integration is important to ensure interoperability. Open technologies and platforms are preferable[Ref 23][Ref 159].
Keywords: Other cross-cutting concepts.

IoT European Large-Scale Pilots (IoT-LSPs): The IoT European Large-Scale Pilots Programme in Horizon 2020's work programme 2016-2017, includes IoT-LSP projects addressing the IoT applications based on European relevance, technology readiness and socio-economic interest in Europe. (ACTIVAGE, MONICA, IoF2020, AUTOPILOT, SYNCHRONICITY, U4IoT, and CREATE-IoT). The IoT-LSPs involve stakeholders from supply side to demand side, and contain all the technological and innovation elements and tasks related to the use, application and deployment, as well as development of technology, testing and integration activities. The pilot projects are also accompanied by coordination and support actions to ensure smooth and efficient cooperation and management of the various activities of the Focus Area (FA) as well as to support cross- fertilisation of the various pilot projects for technological and validation issues of common interest across the various use cases. The European Large-Scale Pilots Programme website is available https://european-iot-pilots.eu/. See also Large-Scale Pilot (LSP) [Ref 182][Ref 183].
Keywords: Other cross-cutting concepts.

IoT European Platforms Initiative (IoT-EPI): A European initiative for IoT platform development, interoperability and information-sharing, founded by the EU to build a vibrant and sustainable IoT ecosystem in Europe. Seven leading research and innovation projects (AGILE, bIoTope, BIG IoT, Inter-IoT, symbIoTe, TagItSmart!, VICINITY) supported by two coordination and support action projects Be-IoT and UNIFY-IoT make their technology accessible to third parties. In addition, a strong support and funding structure in the form of open calls and workshops fosters further collaboration. Their website is available on http://iot-epi.eu/. See also IoT European Platforms Initiative (IoT-EPI)[Ref 184].
Keywords: Collaboration and Process Layer,Other cross-cutting concepts.

IoT Gateway: An Internet of Things (IoT) gateway is a physical device or software program that serves as the connection point between the cloud and controllers, sensors and intelligent device[Ref 185].
Keywords: Other cross-cutting concepts.

IoT Operating Systems: As IoT hardware providers peaked over the past few years, so did IoT Operating Systems (OS) seeing, as they are sometimes tied to a particular platform. There are also some commonly used alternatives, being Linux-based OSbeing the most used alternative these nowadays. IoT OSs are often tied to particular device needs. Therefore, there is not a single approach but multiple options that can be considered depending on the application. Determining if real-time performance is needed, memory size, catching capabilities or CPU processing requirements, level of required security, hardware constraints, and shaping the communication/networking needs are decisive aspects to take into account when choosing the IoT OS[Ref 180][Ref 181].
Keywords: Physical layer.

IoT Platforms: IoT Platforms refer to online management tools for IoT devices, often combining multiple applications such as device management, security, Data Analytics and visualization tools. IoT platforms range from hardware vendor operated (tied to a particular IoT device, network operated (tied to a particular communication network provider) and system integrator operated (offering interoperability approaches)[Ref 180][Ref 181].
Keywords: Service layer, Data.

IoT policy: AIs a document that provides a comprehensive guide to help an organization promote the development of the IoT and/or deal with the complex issues related to that development [Ref 186].
Keywords: Other cross-cutting concepts.

IoT Service: Software component enabling interaction with resources through a well-defi ned interface. Can be orchestrated together with non-IoT services (e.g. enterprise services). Interaction with the service is done via the network.[Ref 187].
Keywords: Other cross-cutting concepts.

IoT Standardization: IoT standardization can be divided into four categories: Platform, Connectivity, Business Model and Killer Applications[Ref 188].
Keywords: Other cross-cutting concepts.

IoT Standards: Standard model to perform common IoT-backend tasks [Ref 188].
Keywords: Application Layer.

IoT Standards Landscape: Support of a large variety of applications departing from existing silos and the generation of healthy ecosystems[Ref 189].
Keywords: Other cross-cutting concepts.

IoT technology: It brings together two evolving technologies: Wireless connectivity and smart sensors[Ref 190].
Keywords: Wireless, Other cross-cutting concepts.

IoT trust|: trust management plays an important role in IoT for reliable data fusion and mining, qualified services with context-awareness, and enhanced user privacy and information security. It helps people overcome perceptions of uncertainty and risk and engages in user acceptance and consumption of IoT services and applications[Ref 191].
Keywords: Other cross-cutting concepts.

IoV: See Internet of Vehicles.

IT: See Information Technology.


J-M

K


Key Enabling Technologies (KET): KETs are a group of six technologies that have a wide range of product applications such as developing low carbon energy technologies, improving energy and resource efficiency, and creating new medical products. They have huge potential to fuel economic growth and provide jobs [Ref 192].
Keywords: Other cross-cutting concepts.

Knowledge economy: Economies which are directly based on the production, distribution and use of knowledge and information. [Ref 193].
Keywords: Other cross-cutting concepts.

Key Performance Indicator (KPI): A KPI is a high-level metric that measures the performance of a company, business unit, project, process or system that aligns with the organisational strategy or the desired outcomes of the process or system in question [Ref 194].
Keywords: Other cross-cutting concepts.

KPI: See Key Performance Indicator.


L


Land parcel identification system (LPIS): This computer database contains all agricultural areas that are eligible for a direct payment under the Common Agricultural Policy. It is used to cross-check the parcels for which payments have been claimed by the farmer. The land parcel identification system ensures that the farmer is paid for the correct area and that overpayment is avoided. [Ref 11]

Liability: Product liability is the area of law in which manufacturers, distributors, suppliers, retailers, and others who make products available to the public are held responsible for the injuries those products cause [Ref 195].
Keywords: Other cross-cutting concepts.

Lifecycle management: Activities related to the follow-up and supervision of the evolution of a system, product, service, project, or other human-made entity from conception through retirement [Ref 196].
Keywords: Other cross-cutting concepts.

Linked Data: Data expressed using W3C’s Resource Description Format, where the URIs for nodes and predicates can be dereferenced to obtain further data/metadata. There is a rapidly expanding set of Linked Open Datasets.
Keywords: Other cross-cutting concepts.

Long-range Wide Area Network (LoRaWAN): The wireless LoRaWAN technology for long-range radio, low power, and low data rate IoT applications are based on spread spectrum chipsets from Semtech Corporation, but promoted by the non-profit association LoRa Alliance. Typical characteristics are distances of up to 20 km, battery- powered end-nodes of up to 10 years’ lifetime, and data rates ranging from 0.3 kbps to 50 kbps in the 869 and 900 MHz ISM bands. Switching between LoRa chirp spread spectrum (CSS) and frequency-shift keying (FSK) modulation are facilitated. The network server hosts the system intelligence and complexity (e.g., duplicate packets elimination, acknowledgement scheduling, data rate adapting). All connections are bidirectional, support multicast operation, and forms a star of stars topology. To serve different applications, the end-nodes are classified in three different classes, which trade off communication latency versus power consumption. Class A is the most energy efficient, and is implemented in all end-nodes. Classes B and C are optional and must be class- A- compatible. A spreading factor (SF) is used to increase the network capacity. A higher SF gives longer communication range, but also implies decreased data rate and increased energy consumption. For frequent data sampling, LoRa systems use an SF as small as possible to limit the airtime, which requires end-nodes located closer to the gateways [Ref 197][Ref 198].
Keywords: 'Network communication layer'

Loss given event (LGE): In operational risk the loss given event (LGE) is the amount of a potential loss in the event of an operational loss event occurring.[Ref 199].
Keywords: Other cross-cutting concepts

LPWAN: LPWAN stands for Low Power Wide Area Network, and refers to the type of wireless network designed to allow long- range communications at low- bit rates, which is especially interesting for the vast great majority of IoT devices. It is also specifically designed for low- power devices, in contrast with other wireless wide- area networks such as Cellular networks, requiring more expensive and power-demanding radio modules, as they allow high- throughput rates. LPWAN technologies can be used to create private networks or a service provided by a third party, eliminating, thus, the need for gateway deployments seeing, as IoT devices can connect directly connect to the network. LPWAN technologies have appeared in the recent past and, evolving into a reality nowadays. The most commonly LPWAN networks/technologies used in Europe, currently are SigFox and LoRa, although NB-IoT is also a promising alternative [Ref 197][Ref 200].
Keywords: Wireless, Network communication layer.

LSP: See IoT Large Scale Pilot Program.


M


M2H: See Machine-to-human

M2M: See Machine-to-Machine

Machine-to-human (M2H) communication: The concept of letting the machines interact with humans based on either voice or gestures is called machine-to-human interaction. See also Human-to-Machine communication [Ref 201].
Keywords: 'Abstraction Layer'

Machine-to-Machine (M2M): Machine- to- machine communications refers to such communications involving just devices (without human intervention) and using any means of communication channels, including wireless. It constitutes a subset of use cases covered by the whole spectrum of IoT cases, as they also include devices triggered or operated by humans. M2M was built from the seed of current IoT and industry 4.0 technology, with networks of machines relaying information back to a central computing system in charge of analysing the information. Currently, those systems evolved into the current usage of M2M to allow systems of networks to transmitting data to personal appliances[Ref 202].
Keywords: Network communication layer.

Manufacturing Digitisation: See Smart Manufacturing

Manufacturing readiness level (MRL): 'Manufacturing readiness level (MRL) is a measure to asses the maturity of manufacturing readiness. The ten MRLs are correlated to the nine TRLs in use, while the final MRL level measures aspects lean practices and continuous improvement for systems in production. The following MRL definitions were developed by a joint DoD (US Department of Defence)/Industry working group: MRL 1: Basic Manufacturing Implications Identified, MRL 2: Manufacturing Concepts Identified, MRL 3: Manufacturing Proof of Concept Developed, MRL 4: Capability to produce the technology in a laboratory environment, MRL 5: Capability to produce prototype components in a production relevant environment, MRL 6: Capability to produce a prototype system or subsystem in a production relevant environment, MRL 7: Capability to produce systems, subsystems, or components in a production representative environment, MRL 8: Pilot line capability demonstrated; ready to begin Low Rate Initial Production (LRIP), MRL 9: Low rate production demonstrated; Capability in place to begin Full Rate Production (FRP), and MRL 10: Full Rate Production demonstrated and lean production practices inplace.[Ref 203].
Keywords: Other cross-cutting concepts

Market: Markets for technology refer to “transactions for the use, diffusion and creation of knowledge and technology". They are places where the technology seller (supply side) meets the technology buyer (demand side). Markets for technology can be characterised along several dimensions, including (i) their purpose, which may be to circulate existing technologies (e.g IP marketplace), or to produce or co-produce new technologies (e.g. based on bilateral contracts); and (ii) the type of technology transactions. Technology transactions can take different forms, from pure licensing or sale of well-defined intellectual property, to complicated collaborative agreements that may include the development of the technology or its realization[Ref 204].
Keywords: Other cross-cutting concepts

Market Adoption Readiness Levels (MARL): A new approach proposed (AIOTI WG2 innovation Ecosystem community) for measuring the impact of early adopter models. This approach poses the increase of TRL as one out of four factors to achieving innovation instead of being the only one. This is a promising starting point for a holistic approach to digital transformation of the EU industry. Such an approach is mostly targeting consumer-centric and creative industries and needs substantial improvements and extensions to be applied to the manufacturing domain. So far, the four factors/levels in this approach are defined as follows: (i) Level of risk, (ii) Number of potential early adopters, (iii) Potential to yield data from early adoption, and (iv) The technology readiness [Ref 23].
Keywords: Other cross-cutting concepts.

Mass customization: Mass customization is a production process that combines elements of mass production with those of bespoke tailoring. Products are adapted to meet a customer's individual needs so no two items are the same. It can also be defined as the production of personalized or tailored goods or services to meet consumers' diverse and changing needs at near mass production prices. Enabled by technologies such as computerization, internet, product modularization, and lean production, it portends the ultimate stage in market segmentation where every customer can have exactly what he or she wants [Ref 205] [Ref 206].
Keywords: Other cross-cutting concepts, physical layer.

Massive Machine Type Communications (mMTC): Massive Machine Type Communications (mMTC) is one of three sets of use cases defined by 3GPP for 5G, (need to support a very large number of devices in a small area, which may only send data sporadically, such as IoT use cases). For other sets of use cases, see eMBB and uRLLC [Ref 207].
Keywords: Wireless, Other cross-cutting concepts.

Middleware: Middleware is a distributed software layer that sits above the network operating system and below the Application Layer and abstracts the heterogeneity of the underlying environment[Ref 208] .
Keywords: Other cross-cutting concepts.

MIMO: Multiple Input Multiple Output technology uses multiple antennae to make use of reflected signals to provide gains in channel robustness and throughput[Ref 209].
Keywords: Network communication layer'

Mobile edge computing: A concept that enables information technology service environments and Cloud computing capabilities at the edge of the radio access networks/Cellular networks. Implementing the relevant applications nearby or at the base stations and thereby performing the processing tasks closer to the users, enables fast and flexible deployment of new context-based applications and services for the users. At the same time, it will relieve traffic in the telecommunications network. MEC is a network infrastructure component for blockchain since the replication of blocks via devices can be implemented at the edge and enables IoT applications to deliver real-time context-based mobile moments to the users. The technical standards are being developed by ETSI. See also Edge Computing [Ref 210] [Ref 23] .
Keywords: Network communication layer

Mobility as a Service (MaaS): MaaS describes a shift away from personally owned modes of transportation and towards mobility solutions that are consumed as a service. The convergence of autonomous vehicles, IoT and AI applications are accelerating the implementation of IoV concept and the move to MaaS.[Ref 211].
Keywords: Other cross-cutting concepts.


N-P

N


Narrow Band IoT: Narrow Band IoT is a LPWAN radio technology standard developed by 3GPP to enable the connection of low-power IoT devices to the Cellular network telecommunication bands. NB-IoT specification was frozen at Release 13 of 3GPP specification (LTE-Advanced Pro) in June 2016. It focuses on indoor coverage enabling long-life battery-powered device applications while increasing the number of connected devices [Ref 212] [Ref 213] .
Keywords: Network communication layer.

Natural Language Processing (NLP): A field of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages and, in particular, concerned with programming computers to fruitfully process large natural language corpora whether written or spoken. NLP is an area of research and application that explores how computers can be used to understand and manipulate natural language text or speech to do useful things [Ref 214].
Keywords: Other cross-cutting concepts.

NB-IoT: See Narrow Band IoT

Near Field Communication (NFC): Standards-based short-range wireless connectivity technology that makes life easier and more convenient for consumers around the world by making it simpler to make transactions, exchange digital content, and connect electronic devices. NFC complements many popular consumerlevel wireless technologies, by utilizing the key elements in existing standards for contactless card technology (ISO/IEC 14443 A&B and JIS-X 6319-4) [Ref 215] .
Keywords: Wireless.

Network: Computer networking is the practice of interfacing two or more computing devices with each other for the purpose of sharing data [Ref 216].
Keywords: 'Network communication layer'

Network Functions Virtualization (NFV): An initiative to virtualize the network services. NFV is way to reduce cost and accelerate service deployment for network operators by decoupling functions like a firewall or encryption from dedicated hardware and moving them to virtual servers [Ref 217] [Ref 218] .
Keywords: 'Network communication layer'

Neural Networks: An information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information [Ref 219] .
Keywords: Processing layer.

Next Generation Networks (NGN): Next Generation Networks are packet-based networks that use IP to transport the various types of traffic (voice, video, data and signalling). The 5G next generation core network is the part of the network that provides services to mobile subscribers through the radio access network (RAN). It is also the gateway to other networks, for instance to the public- switched telephone or to public clouds. [Ref 220].
Keywords: 'Network communication layer'

NFC: See Near Field Communication

NFV: See Network Function Virtualization

NGN: See Next Generation Networks

NLP: See Natural Language Processing

Non-repudiation: An aspect of authentication that enables systems to have a high level of mathematical confidence that data, including identifiers, are genuine. This ensures that either a transmitting or receiving party cannot later deny that the request occurred (cannot later “repudiate”) and provides data integrity around the system. This is of particular importance in terms of tracking illegal activities within an IoT system, as it allows for accountability to be enforced. Whether Non-repudiation needs to be enforced under certain circumstances will depend on the particular applications [Ref 168].
Keywords: AI, IoT, Other cross-cutting concepts


O


OGC SensorThings API model: SensorThings API is an open standard providing a unified framework to interconnect IoT sensing devices, data, and applications over the Web. It is an open standard addressing the syntactic interoperability and semantic interoperability of the IoT [Ref 221] .
Keywords: Data Storage, Other cross-cutting concepts.

OMA NGSI: RESTful API via HTTP whose purpose is to exchange context information[Ref 222] .
Keywords: Other cross-cutting concepts.

oneM2M: A partnership project between the leading telecom standardization organizations in Europe, America and Asia. oneM2M is developing specifications for the service layer for machine-to-machine (M2M) communication and the IoT, and aims to provide common services layer to IoT applications and devices of different service domain/verticals [Ref 223] .
Keywords: Service layer.

Open Data: Open Data is data that can be freely used, re-used and redistributed by anyone subject only, at most, to the requirement to attribute and share alike[Ref 224] [Ref 225] .
Keywords: Other cross-cutting concepts.

Open & Agile Smart Cities (OASC): OASC was founded in 2015 and is a non-profit, international smart city network that has the goal of creating and shaping the nascent global smart city data and services market. Their vision is to create an open smart city market based on the needs of cities and communities [Ref 226].
Keywords: Other cross-cutting concepts.

Open source model: A decentralized software development model that encouraging open collaboration and peer production with products such as source code, blueprints, and documentation freely available to the public.[Ref 227] .
Keywords: Other cross-cutting concepts.

OS: Operating System. See IoT Operating Systems.

Operation technology (OT): Hardware and software that detects or causes a change through the direct monitoring and/or control of physical devices, processes and events in the enterprise [Ref 21].
Keywords: Service layer.

Organisational interoperability: Organisational interoperability is associated with the ability of organisations to effectively communicate and transfer information even across different information systems, infrastructures or geographic regions and cultures. See also Interoperability [Ref 228].
Keywords: Other cross-cutting concepts.

OT: See Operation Technology

Outcome-based Agricultural Services: Agricultural services that are able to deliver not only pure agricultural produces and products, but also quantifiable results that matter to their customers such as crop yield, energy saved, machine uptime, and carbon footprint. Such outcome-based services are possible thanks to the use of technology such as IoT which permits the ability to monitor and control farm processes [Ref 23] .
Keywords: Other cross-cutting concepts, Farming.


P


Paradigm: A paradigm is a standard, perspective, or set of ideas. A paradigm is a way of looking at something [Ref 229] .
Keywords: Other cross-cutting concepts.

Personal data: ‘personal data’ means any information relating to an identified or identifiable natural person (‘data subject’); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person [Ref 230].
Keywords: Other cross-cutting concepts.

Personal data breach: ‘personal data breach’ means a breach of security leading to the accidental or unlawful destruction, loss, alteration, unauthorised disclosure of, or access to, personal data transmitted, stored or otherwise processed [Ref 231].
Keywords: Other cross-cutting concepts.

Personalized Nutrition: Personalized nutrition can be defined as developing unique nutrition guidelines for each individual. Precision nutrition seeks to develop effective approaches based on the combination of an individual's genetic, environmental and lifestyle factors [Ref 232] .
Keywords: Other cross-cutting concepts.

Pervasive: Spreading or spread throughout[Ref 233] .
Keywords: Other cross-cutting concepts.

Physical: Physical refers to tangible objects that are perceived through the senses. Within IoT it refers to the hardware like sensors, devices and networking gear.
Keywords: Physical layer.

Platforms: A platform is a specific combination of hardware and operating system and/or compiler. See also IoT Platforms [Ref 234].
Keywords: Abstraction Layer

Policy and regulations: Technology policy is a form of 'active industrial policy', and effectively argues, based on the empirical facts of technological development as observed across various societies, industries and time periods, that markets rarely decide industrial fortunes in and of their own and state-intervention or support is required to overcome standard cases of market-failure (which may include, for example, under-funding of Research & Development in highly competitive markets) [Ref 235].
Keywords: Other cross-cutting concepts.

Policy on IoT: A document that provides a comprehensive guide to helping an organization promote the development of IoT and/or deal with the complex issues related to that development [Ref 236] .
Keywords: Other cross-cutting concepts.

Precision Agriculture: Precision Agriculture is a whole-farm management approach using information technology, satellite positioning (GNSS) Data, remote sensing and proximal data gathering. These technologies have the goal of optimising returns on inputs whilst potentially reducing environmental impact [Ref 237] .
Keywords: Other cross-cutting concepts.

Precision farming: Precision farming is farm management at a level that allows inputs to be tailored to variable conditions across short distances in a single field [Ref 238] .
Keywords: Other cross-cutting concepts.

Predictive Maintenance: Also called condition-based maintenance, predictive maintenance is a maintenance policy that sets out the regular monitoring of machine and equipment conditions to better understand their operating condition and thus be able to schedule maintenance interventions only when they are really needed. Maintenance interventions are programmed in real-time avoiding unforeseen downtime and their related negative implications. The integration of digital technologies such as IoT in machinery and equipment facilitates predictive maintenance [Ref 23] .
Keywords: Other cross-cutting concepts, industry.

Preventive Maintenance: Time-driven maintenance policy that seeks to correctly predict the optimal times of maintenance interventions in order to anticipate the failure of complex systems. Preventive maintenance results in maintenance interventions scheduled based on the mean-time-to-failure statistic[Ref 23] .
Keywords: Other cross-cutting concepts, Industry.

Privacy: Privacy refers to a person's right to control access to his or her personal data and be free from intrusion, misuse or disclosure by third parties. This definition extends the right of a person to control what is and isn't available on the internet. In the United States of America, privacy is used to refer to Data Protection [Ref 239].
Keywords:AI,IoT

Printed Circuit: A circuit for electronic apparatus made by depositing conductive material in continuous paths from terminal to terminal on an insulating surface [Ref 240] .
Keywords: Physical layer.

Privacy-by-default: Obligation under Art. 25 of the GDPR - By default, only personal data that are essential to the stated purpose of each process shall be processed and that personal data are not made accessible without the individual’s intervention to an indefinite number of natural persons [Ref 241].

Privacy-by-design: Obligation under Art.25 of the GDPR - Privacy should be taken into account throughout the entire engineering process from the earliest design stages to the operation of the productive system i.e. that data protection safeguards (also known as Privacy Enhancing Technologies (PETs)) should be built into products and services from the earliest stage of development [Ref 242]

Proactive Maintenance: In opposition to corrective (reactive) maintenance, proactive maintenance seeks to detect and correct the root cause aberrations of failure (unstable operating conditions that will lead to actual failure unless they are corrected)[Ref 243] .
Keywords: Other cross-cutting concepts.

Processing: ‘processing’ means any operation or set of operations which is performed on personal data or on sets of personal data, whether or not by automated means, such as collection, recording, organisation, structuring, storage, adaptation or alteration, retrieval, consultation, use, disclosure by transmission, dissemination or otherwise making available, alignment or combination, restriction, erasure or destruction [Ref 244] .
Keywords: Other cross-cutting concepts.

Production Systems: A manufacturing subsystem that includes all functions required to design, produce, distribute, and service a manufactured product [Ref 245].
Keywords: Application Layer.

Programme: A plan of activities to be done or things to be achieved [Ref 246].
Keywords: Other cross-cutting concepts.

Profiling: ‘profiling’ means any form of automated processing of personal data consisting of the use of personal data to evaluate certain personal aspects relating to a natural person, in particular to analyse or predict aspects concerning that natural person’s performance at work, economic situation, health, personal preferences, interests, reliability, behaviour, location or movements [Ref 247] .
Keywords: Other cross-cutting concepts.

Prosumer: In the 1980 book, The Third Wave, futurologist Alvin Toffler coined the term "prosumer" when he predicted that the role of producers and consumers would begin to blur and merge. George Ritzer and Nathan Jurgenson, in a widely-cited article, claim that prosumption has become a salient characteristic of Web 2.0. Prosumers create value for companies without receiving wages. Sparked by technology and led by global consumer culture's dominance, 21st-century consumption has been radically transformed; co-creation and prosumption being some of its most representative examples. The prosumer actively works to produce the services and goods they buy and consume. For example: self-check-outs at the supermarket, the DIY furniture of Ikea, or online order and delivery services such as E-bay or Amazon. In fact, with the huge help of the Internet, most prosumption is happening in the online world. The most common example is Wikipedia where the users can generate, edit, update and comment on articles. Nevertheless, it is not enough to create stimulating contexts and environments for consumers to take an active role. For prosumption to be integrated in technological development in IoT at a significant level, commitment of prosumers is key. Commitment is a limited resource in a context where “consumer fatigue” – consumers frustrated by technological solutions that they no longer understand and whose utility they no longer perceive – is an encompassing trend in consumer research[Ref 248][Ref 249] [Ref 250] [Ref 251].
Keywords: Other cross-cutting concepts.

Public-Private Partnership (PPP): PPP is a long-term agreement, cooperation, and collaboration between two or more public and private sectors. In EU the PPPs are based on roadmaps for research and innovation activities which are the result of an open consultation process. [Ref 252] .
Keywords: Other cross-cutting concepts.


Q-S

Q


QoS: See Quality of Service

QR Codes: A QR code is a type of matrix (or bi-dimensional, BiDi) barcodes. Barcodes are machine-readable, optical labels including relevant information about the object to which it is attached. A QR code can encode its information using four different and standardized modes, namely kanji, alphanumeric, numeric and byte/binary, although extensions can also be used. QR codes are specifically designed for cameras to read. It is commonly presented as small black squares arranged in a square grid on a white background. QR codes are especially interesting for IoT as they enable device identification and interaction with other devices or human users [Ref 253] .
Keywords: Physical layer.

Quantum computers: Quantum computers are different from transistor-based computers and use atomic quantum states to effect computation. Data are held in quantum bits (qubits), which can hold all possible states simultaneously (superposition) and give the ability to operate exponentially fast due to increased word length. Quantum bits affect each other even when physically separated (entanglement). Achieving both superposition and entanglement is extremely challenging[Ref 254] .
Keywords: Other cross-cutting concepts.

Quality of Service (QoS): Quality of Service refers to the measurement of the performance, usually observed user-side, of services such as telephony, Cloud, computer or IoT networks. This assessment includes several aspects such as latency, error rate, throughput and availability. Quality of Service is relevant to any IoT network whose applications are oriented toward interactions with humans. They should perceive smooth communication and critical or real-time operations where delays and error rates should be minimized [Ref 181].
Keywords: Network communication layer.

Quality of Experience (QoE): A measure of the overall level of customer satisfaction with the network as measured by various success factors including ease of use, reliability, security, and cost. .
Keywords: Application Layer, Other cross-cutting concepts.

R


Radio Access Network (RAN): The part of the telecommunications network that connects user equipment to other parts of a mobile network via a radio connection. Connects user equipment to the core network.
Keywords: Other cross-cutting concepts.

Radio Access Technology (RAT): The underlying physical connection method for a radio-based communication network. Modern phones may support several RATs in one device such as Bluetooth, Wi-Fi, NFC (Near-Field Communications), and 3G, 4G or LTE, and 5G.
Keywords: Other cross-cutting concepts.

RAMI: RAMI 4.0 stands for Reference Architectural Model Industrie 4.0. RAMI 4.0 is a service-oriented architecture that combines all elements and IT components using a layer and life cycle model. RAMI 4.0 breaks down complex processes into easy-to-grasp packages along three dimensions: hierarchy levels (related to the systems, machines and products present in the factory), the product life cycle and a layered architecture [Ref 255] .
Keywords: Service layer.

Reasonable: Reasonable refers mainly to the licensing rates. According to some, a reasonable licensing rate is a rate charged on licenses which would not result in an unreasonable aggregate rate if all licensees were charged a similar rate [Ref 256] .
Keywords: Other cross-cutting concepts.

Reference Architecture Model: A reference model that provides an architectural template solution for a particular domain. Concerning IoT, there is a need to standardize a reference architecture model in order to support the interoperability in IoT. In this context, the IoT platforms are the highest, most generalized layer of intelligence and user interface that ties together connected devices and web-based services. They collectively define a reference architecture model for IoT. A wide range of technologies, communication protocols, layers, dimensions and standards are taken into consideration. An example of a reference architecture model initiative is Industrie 4.0 (RAMI). See also Architecture and Industrie 4.0 [Ref 257] [Ref 153] .
Keywords: Other cross-cutting concepts.

Regulation : Regulations can refer to either specific European Law or a more general description. In European Law, a regulation is a legal act adopted by the European institutions and are legally binding with immediate application in all member states providing homogenous application of EU law across states. Generally, a regulation is the application of a set of standards, norms and/or responsibilities overseen by an external body (i.e. government) or internally (e.g. industry body)to ensure the maintenance of quality or proper functioning of a product, service or market and to support consistency across jurisdictions [Ref 258] [Ref 259]. Keywords: Other cross-cutting concepts

Reliability: Enables IoT systems to operate without systems outages and regular human intervention. Reliability is essential for productivity and is a key prerequisite for AI systems that are put into continuous operation with short maintenance time in mission-critical production environments [Ref 260].
Keywords: AI,IOT

Research: Systematic investigative process employed to increase or revise current knowledge by discovering new facts. It is divided into two general categories: (i) Basic research is inquiry aimed at increasing scientific knowledge. (ii) Applied research is effort aimed at using basic researchfor solving problems or developing new processes, products, or techniques [Ref 261] .
Keywords: Other cross-cutting concepts.

Resilience: Enables IoT with embedded AI to always operate in stable states, including to return to such states after failures. Resilience is essential for their safe support for our digital economy. In the future, they should even be able to detect failure and initiate measures for compensating it [Ref 262]. See also AI and IoT
Keywords: Other cross-cutting concepts

Resource Description Framework (RDF): Resource Description Framework (RDF)[Ref 263] .
Keywords: Other cross-cutting concepts.

Resource virtualization: Resource virtualization consists in either partitioning a single physical resource into multiple virtual resources or aggregating multiple physical resources into one virtual resource [Ref 264].
Keywords: 'Abstraction Layer'

Reverse Proxy Server (RPX): An RPX is a type of proxy server, typically sits behind a firewall and directs requests to the back-end server. A reverse proxy ensures the flow of network traffic between clients and servers. It also ensures that multiple servers can be accessed from a single URL regardless of the structure of local area network. An RPX can sit in front of back-end servers and distribute client requests across a group of servers to maximize speed and capacity utilization, ensuring that no single server is overloaded, thus maintaining the performance. If a server goes down, the load balancer redirects traffic to the remaining online servers.
Keywords: 'Other cross-cutting concepts'

RFID: RFID stands for Radio Frequency identification and refers to a system of storing and retrieving data wirelessly using tags, smart cards or RFID transponders. It uses electromagnetic fields to identify tags attached to objects which should be brought into proximity of a reader with a typical coverage of a couple of centimetres. tags can be passive (unpowered and just readable when close enough) or active (battery powered and with extended coverage). RFID is commonly embedded into IoT applications and deployments as an easy way to identify devices and/or interact with humans [Ref 265] [Ref 266] .
Keywords: Physical layer.

Risk: Potential that a given threat will exploit vulnerabilities of an asset or group of assets to cause loss or damage to the assets [Ref 267] .
Keywords: Other cross-cutting concepts.

Robotics: Branch of science that deals with making and using robots.[Ref 268]
Keywords: Other cross-cutting concepts.

Roadside unit (RSU): RSUs are computing and communication equipment located on the roadside and provide connectivity support to the passing vehicles. [Ref 269] .
Keywords: Automotive,Other cross-cutting concepts.

Robotic things: See Internet of Robotic things (IoRT)


S


Scalability: An attribute that describes the ability of a process, network, software or organization to grow and manage increased demand. Scalability is often a sign of stability and competitiveness, as it means the network, system, software or organization is ready to handle the influx of demand, increased productivity, trends, changing needs and even presence or introduction of new competitors.[Ref 270] .
Keywords: Other cross-cutting concepts.

SCRAL: The SCRAL is an adaptation layer that provides a REST-based uniform and transparent access to physical devices, systems and services for monitoring and actuation purposes.
Keywords: Other cross-cutting concepts.

Safety: In IT systems, it refers to functional safety (in the physical not digital dimensions) [Ref 271].
Keywords: AI,IoT

SDN: See Software Defined Network

Seamless integration: The process where a new module or feature of an application or hardware is added or integrated without resulting in any discernable errors or complications.[Ref 272] .
Keywords: Application Layer.

Secure Update: Enables IoT systems and devices to install new firmware from authorized sources without the firmware being compromised. Software updates are critical processes and are susceptible to a number of threats and attacks. During an update, the device receives the firmware wirelessly and installs it, removing the previous version. However, to reassure that the process is being done properly and securely, the sender of the firmware should be verified as trusted, the firmware should be validated as not compromised, the initial security keys should be protected, etc. Additionally, depending on the services that the device offers, the downtime during a firmware update may need to be kept at a minimum. If not properly protected, devices may be open to manipulation, typically through the installation of malicious code on a device [Ref 273]. Keywords: AI,IoT

Security-by-Default: A system is secure by default when the default settings put the system in a secure state. To prevent unauthorized physical access, damage and interference to the organization's information and information processing facilities, security perimeters should be defined and used to protect areas that contain either sensitive or critical information and information processing facilities[Ref 274].
Keywords: Security.

Security-by-Design: The capability of an ICT product to protect information and data so that unauthorised persons or systems cannot read or modify them and authorised persons or systems are not denied access to them[Ref 275].
Keywords: Other cross-cutting concepts.

Security Fusion Node: Security Fusion Node is a lightweight multithreaded REST API responsible for forwarding messages from the edge up to the cloud, and adding additional information where required. The Security Fusion Node acts as an interface between the outputs of the algorithms and the higher-level services.
Keywords: Other cross-cutting concepts.

Semantic interoperability: Semantic interoperability is associated with shared understanding of the meaning of the exchanged content/ information). (See also Interoperability).[Ref 276].
Keywords: Other cross-cutting concepts.

Self-healing: Self-healing can be defined as the property that enables a system to perceive that it is not operating correctly and, without (or with) human intervention, make the necessary adjustments to restore itself to normality [Ref 277].
Keywords: Other cross-cutting concepts.

Self-optimizing: The conceivable development of information technology will enable mechatronic systems with inherent partial intelligence. We call this kind of systems self-optimizing [Ref 278].
Keywords: Other cross-cutting concepts.

Self-protecting: Self-protecting software systems are a class of autonomic systems capable of detecting and mitigating security threats at runtime [Ref 279].
Keywords: Other cross-cutting concepts.

Services: Services are intangible products provided to a customer or user enabling them to achieve a task or goal.
Keywords: Other cross-cutting concepts.

Service provider: A person or another entity that has the overall responsibility for the provision of a service or a set of services to the users and for negotiating network capabilities associated with the service(s) he/she provides [Ref 280].
Keywords: Other cross-cutting concepts.

Silver economy: Existing and emerging economic opportunities associated with the growing public and consumer expenditure related to population ageing and the specific needs of the population over 50 [Ref 281].
Keywords: Other cross-cutting concepts.

Smart Buildings: Smart building encompass many things, but, the primary goal is the use of building technology systems to enable enhanced services and the efficient operation of a building for the betterment of its occupants and building management. The main drivers of smart buildings are the positive financial impacts of integrated system, energy conservation, greater systems functionality, and the continuing evolution of technology [Ref 282].
Keywords: Other cross-cutting concepts.

Smart City: Smart city refers to those Cities integrating Information Technologies together with IoT technology to gather and monitor data from its assets (including hospitals, power plants, transportation systems, local information systems and water supply networks) and citizens. The data gathered is used to optimize the services being monitored and enhance quality of life for all citizens [Ref 283].
Keywords: Application Layer, Applications.

Smart Clothing: Life simulation system which has perception and feedback of clothing. Smart clothing can sense changes in internal and external environmental conditions, as well as make real-time or near-time self-report feedback[Ref 284].
Keywords: Other cross-cutting concepts.

Smart energy: Smart energy system is defined as an approach in which smart electricity, thermal and gas grids are combined and coordinated to identify synergies between them in order to achieve and optimal solution for each individual sector as well as for the overall energy system [Ref 285].
Keywords: Other cross-cutting concepts.

Smart Environments: Any space where ubiquitous technology informs the learning process in an unobtrusive, social or collaborative manner[Ref 286].
Keywords: Other cross-cutting concepts.

Smart Farming: Smart farming techniques help produce more food from fewer resources, including soil, water, fertilisers, pesticides and human effort. Predictive Analytics helps improve yields, reduce crop diseases and optimise resource utilisation. Smart farming concept brings together researches, farms and industry to produce food smarter [Ref 287].
Keywords: Other cross-cutting concepts.

Smart Grid: The Smart Grid is the evolution of the current electrical grid. The electricity network is based on digital technology that is used to supply electricity to consumers via two-way digital communication. The Smart Grid allows for monitoring, analysis, control and communication to help improve efficiency, reduce energy consumption and cost, and maximize the transparency and reliability of the energy supply chain. [Ref 288].
Keywords: Other cross-cutting concepts.

Smart Health: The technology that leads to better diagnostic tools, better treatment for patients, and [[#Device|devices] that improve the quality of life for anyone and everyone[Ref 289].
Keywords: Other cross-cutting concepts.

Smart Homes: Smart Home technology has become the popular name for the integration of telematics into the electrical installation of the home [Ref 290].
Keywords: Application Layer.

Smart living: Smart living refers to improving quality of life by transforming environments to become more intelligent and adaptable to users [Ref 291].
Keywords: Application Layer.

Smart living environments: A physical world that is richly and invisibly interwoven with sensors, actuators, displays, and computational elements, embedded seamlessly in the everyday objects of our lives, and connected through a continuous network[Ref 292].
Keywords: Application Layer.

Smart Manufacturing: Smart manufacturing is a broad category of manufacturing with the goal of optimizing concept generation, production, and product transaction. While manufacturing can be defined as the multi-phase process of creating a product out of raw materials, smart manufacturing is a subset that employs computer control and high levels of adaptability. Smart manufacturing aims to take advantage of advanced information and manufacturing technologies to enable flexibility in physical processes to address a dynamic and global market. There is increased workforce training for taking advantage of the increased flexibility of this technology instead of the specific tasks that are customary in traditional manufacturing [Ref 293].
Keywords: Application Layer.

Smart Mobility: Technology that enables Intelligent Transport Systems to create highly efficient, uninterrupted and reliable transportation networks with the goal to build sustainable infrastructure for future generations [Ref 294]
Keywords: Other cross-cutting concepts.

Smart Objects: A smart object is an item equipped with a form of sensor or actuator, a tiny microprocessor, a communication device, and a power source [Ref 295].
Keywords: Physical layer.

Smart sensor: An advanced platform with onboard technologies such as microprocessors, storage, diagnostics, and connectivity tools that transform traditional feedback signals into true digital insights. Smart sensors can provide the timely and valuable data underpinnings to power analytical insights that can in turn drive improvements in cost, performance, or customer experience [Ref 296].
Keywords: Other cross-cutting concepts.

Smart Watch: A smartwatch is a wearable computer in the form of a wristwatch; modern smartwatches provide a local touchscreen interface for daily use, while an associated smartphone app provides for management and telemetry [Ref 297].
Keywords: Other cross-cutting concepts.

Smart Water Management: Utility system for water supply which is characterized by the use of communication networks and the control of grid components and loads [Ref 298].
Keywords: Other cross-cutting concepts.

Social innovation: Social innovations are new ideas that meet social needs, create social relationships and form new collaborations. A considerable number of technology-based artworks, transformed into products and services, were conceived to be products from conception; not necessarily due to potential commercial reasons but instead were designed so as to have an impact on society. In this context, social innovation is a relevant aspect in IoT. Projects such as the open hardware platform Arduino show how artistic practice can lie at the basis of later technological developments with a tangible economic and societal impact. They have a concrete impact on the growth and jobs objective by enabling more people to experiment with open source digital technology. This exponentiates the probability of the creation of new products and services and contributes to socially-driven innovation processes which distinguish the EU from other players in the global market [Ref 299][Ref 26].
Keywords: Other cross-cutting concepts.

Sound Field Control System: The Sound Field Control System (SFC) is a loudspeaker (secondary source) array driven by sensibly calculated multi-channel signals based on a pre-obtained sound propagation model [Ref 299][Ref 26].
Keywords: Other cross-cutting concepts.

Software Defined Network: Novel network paradigm that separates each network services from its point of attachment to the network, creating a far more dynamic, flexible, automated, and manageable architecture. It is an emerging architecture that is dynamic, manageable, cost-effective, and adaptable, making it ideal for the high-bandwidth, dynamic nature of today’s applications [Ref 300].
Keywords: Network communication layer

Standardisation: See Standard

Stakeholder: An individual or organization that is affected by the development or implementation of a project [Ref 280].
Keywords: Other cross-cutting concepts.

Standard developing organization (SDO): SDOs are standards bodies whose primary activities are developing, coordinating, promulgating, revising, amending, reissuing, interpreting, or otherwise producing standards [Ref 301].
Keywords: Standard,Other cross-cutting concepts.

State-of-the-art (SOTA): SOTA refers to the highest level of development achieved at a particular time regarding devices, techniques, methodologies, scientific fields, etc [Ref 288].
Keywords: Other cross-cutting concepts.

STARTS: The European Commission has launched a new initiative, (S+T)*ARTS=STARTS - innovation at the nexus of Science, Technology and the ARTS. STARTS funds and encourages collaboration of the Arts with Technology by, for instance, including artists in H2020. The mission of STARTS is to bring artists into innovation. An innovation that is much more than the sum of its parts and goes well beyond: Holistic innovation. In fact, in order to create value for citizens, industry has to think more holistically about technologies and services that put the human in the centre. Indeed, digital transformation of industry and society is already naturally uniting science and engineering with design and artistic approaches. This can be seen in many areas where art and technology naturally collaborate like in urban development or in new media like virtual and augmented reality. In this context, the Arts gain prominence as catalysts for an efficient conversion of S&T knowledge into radical novel products, services, and processes [Ref 302].
Keywords: Other cross-cutting concepts.

Strategic Research and Innovation Agenda (SRIA): The purpose of the SRIA is to lay down guiding principles and identify research priorities for the future, while making them openly accessible to the various stakeholder groups including the policy makers, regulatory agencies, researchers, end-users, and public [Ref 303].
Keywords: Other cross-cutting concepts.

Supply Chain Management: The management of the flow of goods and services; defined as the "design, planning, execution, control, and monitoring of supply-chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply with demand and measuring performance globally [Ref 304].
Keywords: Other cross-cutting concepts.

Syntactic interoperability: Syntactic interoperability is usually associated with data formats and encodings (e.g., XML, JSON and CSV) along with techniques for compressing them. See also Interoperability[Ref 305].
Keywords: Other cross-cutting concepts.

Swarm intelligence (SI): This concept can be looked at as a subfield of artificial intelligence (AI) and is based on collective behaviour and interaction of decentralized and self-organized systems inspired by nature ("swarm of individuals"). With enhanced SI, IoT objects are capable of cooperating and sharing resources efficiently (by a set of algorithms). This allows for solving numerous IoT optimization challenges, which are otherwise difficult to implement due to the large resources required. Examples of IoT applications may be optimization of node localization, signal coverage, and transmission route [Ref 23].
Keywords: Other cross-cutting concepts.

Swarm technologies: The technologies that provide swarm intelligence (SI). The swarm technologies needed are related to the applications. Together with the artificial intelligence, robotics, and machine learning; the swarm technologies are the technologies that will provide the next phase of development of IoT applications[Ref 23].
Keywords: Other cross-cutting concepts.

Systems of systems: Combination of systems (being individually composed of interacting elements) organized to achieve one or more stated purposes. Note 1: A system may be considered as a product and/or as the services it provides. Note 2: In practice, the interpretation of its meaning is frequently clarified by the use of an associative noun, e.g. aircraft system [Ref 306].
Keywords: Collaboration and Process Layer.


T-Z

T


Tactile IoT/IIoT:The Tactile IoT/IIoT is a shift in the collaborative paradigm, adding human-centred perspective and sensing/actuating capabilities transported over the network to communications modalities, so that people and machines no longer need to be physically close to the systems they operate or interact with as they can be controlled remotely. Tactile IoT/IIoT combines ultra-low latency with extremely high avail- ability, reliability and security and enables humans and machines to interact with their environment, in real-time, using haptic interaction with visual feedback, while on the move and within a certain spatial communication range. The Tactile IoT/IIoT provides the capabilities to enable the delivery of real-time control and physical (haptic) experiences remotely. The capabilities of the Tactile IoT/IIoT support the creation of a personal spatial safety zone, which is able to interact with nearby objects also connected to the Tactile IoT/IIoT. If applied to traffic, in the long term, this safety zone will be able to protect drivers, passengers and pedestrians. Autonomous vehicles could detect safety-critical situations and react instantly to avoid traffic accidents and warn other objects of impending danger. In produc- tion environments, occupational safety levels will improve as production machines or robots detect and avoid the risk of harm to people in their vicinity [Ref 307].
Keywords: Other cross-cutting concepts.

Technical interoperability: Technical interoperability is usually associated with communication protocols and the infrastructure needed for those protocols to operate. See also Interoperability [Ref 308].
Keywords: Other cross-cutting concepts.

Technology: Technology is a body of knowledge devoted to creating tools, processing actions and extracting of materials [Ref 309].
Keywords: Other cross-cutting concepts.

Technology Readiness Level (TRL): A tool for describing the maturity of a technology. The scale ranges from level 1 to level 9, where each level characterises the technology development progress, from idea to product. The European Commission defines the nine Technology Readiness Levels as follows: TRL 1: Basic principles observed, TRL 2: Technology concept formulated, TRL 3: Experimental proof of concept, TRL 4: Technology validated in lab, TRL 5: Technology validated in relevant environment (industrially relevant environment in the case of key enabling technologies), TRL 6: Technology demonstrated in relevant environment, (industrially relevant environment in the case of key enabling technologies), TRL 7: System prototype demonstration in operational environment, TRL 8: System complete and qualified, and TRL 9: Actual system proven in operational environment, (competitive manufacturing in the case of key enabling technologies; or in space) [Ref 310].
Keywords: Other cross-cutting concepts.

Tensorflow Lite: Lightweight AI/ML framework. Feasible to be used in IoT Edge and IoT devices [Ref 311].
Keywords: ML, AI, Tensor Flow, Framework.

Test beds: An execution environment configured for testing. May consist of specific hardware, OS, network topology, configuration of the product under test, other application or system software, etc. The Test Plan for a project should enumerate the test beds to be used [Ref 312].
Keywords: Other cross-cutting concepts.

Things: A thing, in the Internet of things, can be a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors to alert the driver when tire pressure is low - or any other natural or man-made object that can be assigned an IP address and provided with the ability to transfer data over a network [Ref 313].
Keywords: Physical layer.

TPU: Tensor Processing Unit. Coprocessor included in IoT Edge and IoT devices to enhance AI/ML processing. [Ref 314].
Keywords: ML, AI, Tensor Flow .

Transdisciplinary: Transdisciplinary research is defined as research efforts conducted by investigators from different disciplines working jointly to create new conceptual, theoretical, methodological, and translational innovations that integrate and move beyond discipline-specific approaches to address a common problem. Transdisciplinarity requires for creating a unity of intellectual frameworks beyond the disciplinary perspectives, whilst interdisciplinarity integrates knowledge and methods from different disciplines using a real synthesis of approaches. Transdisciplinarity can also be found in the arts and humanities. For example, the Planetary Collegium seeks "the development of transdisciplinary discourse in the convergence of art, science, technology and consciousness research[Ref 315].
Keywords: Other cross-cutting concepts.

Transfer Learning: AI/ML technique that allows to retrain, a currently existing pre-trained model, with an IoT Edge device. This allows AI smart services in the edge for quick adaptations and not depending on a cloud service or internet connectivity of your IoT devices. Special processing units are required because of the high demanding processing for the training [Ref 316].
Keywords: ML, AI.

Transmission range: How long/distance an IoT sensor, edge device or gateway can send/receive communication [Ref 317].
Keywords: Other cross-cutting concepts.

Transparent: Network transparency is the situation in which an operating system or other service allows a user to access a resource (such as an application program or data) without the user needing to know, and usually not being aware of, whether the resource is located on the local machine (i.e., the computer which the user is currently using) or on a remote machine (i.e., a computer elsewhere on the network) [Ref 318].
Keywords: AI, IoT, Network communication layer

Trust: Relationship between two elements, a set of activities and a security policy in which element x trusts element y if and only if x has confidence that y will behave in a well-defined way (with respect to the activities) that does not violate the given security policy [Ref 319].
Keywords: Collaboration and Process Layer.

Trust Management: Trust-Management systems provide applications with a standard interface for getting answers to such questions, and provide users with a standard language for writing the policies and credentials that control what is allowed and what isn't [Ref 320].
Keywords: Standard, Collaboration and Process Layer.

Trusted IoT: The development of standards for trust, privacy and end-to-end security for the Internet of things [Ref 321].
Keywords: Other cross-cutting concepts.

Trustworthy: Trustworthiness is the demonstrated ability of the trustee to perform a specified action while adhering to a set of stated principles (integrity) and acting in the best interest of the trustor (benevolence) [Ref 322].
Keywords: AI, IoT, Other cross-cutting concepts


U


Ultra-Reliable Low Latency Communications (uRLLC): Ultra-Reliable Low Latency Communications (uRLLC) is one of three sets of use cases defined by 3GPP for 5G, (strict requirements on latency and reliability for mission critical communications, such as remote surgery, autonomous vehicles or the Tactile Internet). For other sets of se cases, see eMBB and mMTC [Ref 323].
Keywords: Wireless, Other cross-cutting concepts.

Urban farming: The growing of crops and raising of livestock within an urban environment for consumption within the local area. Activities include, among others, balcony, rooftop and back garden growing, community gardens, allotment gardening and animal grazing on commons [Ref 324].
Keywords: Other cross-cutting concepts.


Uu interface: The radio/air interface between the mobile and the radio access network [Ref 325].
Keywords: Network communication layer.


V


Value Chain: The value chain refers to all the activities, from receipt of raw materials to post-sales support that together create and increase the value of a product [Ref 326].
Keywords: Other cross-cutting concepts.

Value Network: The collection of upstream suppliers, downstream channels to market, and ancillary providers that support a common business model within an industry. When would-be disruptors enter into existing value networks, they must adapt their business models to conform to the value network and therefore fail at disruption because they become co-opted [Ref 327].
Keywords: Other cross-cutting concepts.

Vehicle-to-Cloud (V2C) communication: Wireless exchange of information between vehicles and the cloud (or edge computing centres), for instance used for tracking and usage-based insurance [Ref 328].
Keywords: Automotive, Other cross-cutting concepts.

Vehicle to device (V2D): Communication model that allows the exchange of information between a vehicle and any electronic device that may be connected to the vehicle itself [Ref 317].
Keywords: Other cross-cutting concepts.

Vehicle to everything (V2X): Communication model that allows the passing of information from a vehicle to any entity that may affect the vehicle, and vice versa[Ref 329].
Keywords: Automotive, Other cross-cutting concepts.

Vehicle-to-Grid (V2G) communication: Wireless or wired exchange of information between electric vehicles and the charging station/power grid for such as battery status and correct charging and energy storage and power grid load/peak balancing [Ref 328].
Keywords: Automotive, Other cross-cutting concepts.

Vehicle-to-Home (V2H) communication: Wireless exchange of information between vehicles and a fixed or temporarily home, for instance used for real-time routing [Ref 328].
Keywords: Automotive, Other cross-cutting concepts.

Vehicle-to-Infrastructure (V2I) communication: Two-way wireless transmission of information (data) between vehicles and the roadside infrastructure, e.g. embedded equipment in traffic signs/lights. The main components are the on-board unit, roadside equipment and reliable communication channel. V2I communication facilitates local (or regional) traffic coordination. Information on traffic and road conditions can be used to inform, warn or redirect vehicles to a given area. Information from the vehicles can also be collected and redistributed to ensure traffic safety, avoid traffic congestion, improve traffic flow and environment, collect road toll, etc. Interconnectivity between vehicles and the infrastructure play an important role in intelligent transportation systems (ITS) and autonomous driving. High-speed environments and reliable real-time information are important issues for the V2I communication network. Examples on relevant standards are ETSI ITS-G5, IEEE 802.11p, IEEE 1609, and SAE J2735 [Ref 330].
Keywords: Wireless, Other cross-cutting concepts.

Vehicle-to-Maintenance (V2M) communication: Wireless exchange of information between the vehicle and the vehicle condition responsible (automotive manufacturer or repair shop), including vehicle condition monitoring, predictive maintenance notification or alerts[Ref 328].
Keywords: Automotive, Other cross-cutting concepts.

Vehicle-to-Network (V2N) communication: Wireless exchange of information between vehicles and cellular networks, used for value added services such as traffic jam information and real-time routing or available charging stations for electric vehicles (EVs) [Ref 328].
Keywords: Automotive, Other cross-cutting concepts.

Vehicle-to-Owner (V2O) communication: Wireless exchange of information between vehicles and its owner. Use cases may be car rental, fleet management, freight tracking, etc.)[Ref 328].
Keywords: Automotive, Other cross-cutting concepts.

Vehicle-to-pedestrian (V2P) communication The wireless transmission of information (data) between the vehicles and pedestrians (usually including bicyclists and other VRUs).
Keywords: Automotive, Other cross-cutting concepts.

Vehicle-to-Users (V2U) communication: Wireless or wired exchange of information between the vehicle and its current user including situational information [Ref 328].
Keywords: Automotive, Other cross-cutting concepts.

Vehicle-to-Vehicle (V2V) communication: The wireless transmission of information (data) between vehicles. V2V communication facilitates exchange of information and early warnings/control to ensure traffic safety, avoid traffic congestion, improve traffic flow and environment, etc. Interconnectivity between vehicles plays an important role in autonomous driving. High-speed environments and reliable real-time information are important issues for the V2V ad-hoc communication network, also referred to as VANETs (vehicular ad-hoc networks) or IVC (inter-vehicle communication). Examples on relevant standards are ETSI ITS-G5, IEEE 802.11p, IEEE 1609, and SAE J2735 [Ref 331].
Keywords: Wireless,Other cross-cutting concepts.

Vehicular Visible Light Communication (VVLC): VVLC is using visible light for data communication. The increasing use of LEDs and its short response time opens for complementary communication solutions and new applications [Ref 332].
Keywords: Automotive, Other cross-cutting concepts.

Verifiability: Enables IoT and AI-based systems to demonstrate the functionality and properties they are supposed to have. AI systems for industrial applications must fulfil the same standards as legacy systems and will be applied to safety-, mission- and business-critical tasks. This requires that AI embedded systems can be validated (to reach correct results), verified (verifiable AI) and certified (certifiable AI) for the targeted applications [Ref 333].
Keywords: AI, IoT, Other cross-cutting concepts

Virtual: Representation of an asset in the cyberspace. NOTE: In this context, currency can be defined as either a medium of exchange or a property that has value in a specific environment, such as a video game or a financial trading simulation exercise [Ref 334].
Keywords: Other cross-cutting concepts.

Virtual Food Chains: The digital representation (virtual) of a supply chain, enabled by the use of digital technologies such as IoT. The use of virtual food chains enables the application of virtual chain management techniques such as advanced remote planning, re-planning, monitoring and control of the different elements and processes involved across the chain [Ref 23].
Keywords: Collaboration and Process Layer, Agrifood.

Virtual Manufacturing: A virtual manufacturing system is a computer system that can produce similar information concerning manufacturing system structure, states and behaviours as one can observe in the real manufacturing systems it represents [Ref 335].
Keywords: Processing layer.

Virtual Reality (VR): Virtual Reality provides a computer-generated 3D environment that surrounds a user and responds to that individual’s actions in a natural way, usually through immersive head-mounted displays and head tracking. Gloves providing hand-tracking and haptic (touch sensitive) feedback may be used as well. Room-based systems provide a 3D experience for multiple participants; however, they are more limited in their interaction capabilities[Ref 21].
Keywords: Application Layer, Physical layer.

Virtualisation: The process of changing something that exists in reality into a virtual version. The abstraction of information technology (IT) resources that masks the physical nature and boundaries of those resources from resource users. An IT resource can be servers, clients, storage, networks, applications or operating systems. Essentially, any IT building block can potentially be abstracted from resource users [Ref 336][Ref 21].
Keywords: Other cross-cutting concepts.

Vulnerable road user (VRU): VRUs are non-motorised road users, such as pedestrians, bicyclists and horse riders as well as persons with disabilities or reduced mobility/ orientation, and even motorcyclists [Ref 337].
Keywords: Other cross-cutting concepts.


W


W3C (World Wide Web Consortium): International community that develops open standards to ensure the long-term growth of the Web [Ref 331].
Keywords: Other cross-cutting concepts.

Web Content Accessibility Guidelines (WCAG): Explains how to make web content more accessible to people with disabilities [Ref 338].
Keywords: Other cross-cutting concepts.

Web Hub: Application server and gateway for the Web of Things for applications that produce or consume things. Server-side applications can expose IoT devices as things using common Web protocols, hiding the details of the IoT technologies at the network edge.
Keywords: Other cross-cutting concepts.

Web of Things (WoT): A term used for fully integration of physical objects with the web. Physical objects like smart devices will be able to communicate with each other using existing Web standards. The WoT provides an application layer that simplifies the creation of IoT applications. W3C has launched the Web of Things Working Group to develop initial standards for the WoT to reduce fragmentation [Ref 339].
Keywords: Application Layer.

Wearables: Wearable refers to all electronic devices able to be worn on the human body using implants or through the use of clothing and accessories. They are often designed to track activity and/or health-related measurements. They are IoT devices optimized to be ultra-low cost, size and power. They are thought to constantly interact with the user [Ref 340].
Keywords: Physical layer.

Wellness: The optimal state of health of individuals and groups. There are two focal concerns: the realization of the fullest potential of an individual physically, psychologically, socially, spiritually and economically; and the fulfilment of one's expected role in the family, community, place of worship, workplace and other settings [Ref 341].
Keywords: Other cross-cutting concepts.

Wireless personal area network (WPAN): WPAN is based on low-power and low-range communication technologies specified through IEEE 802.15 (e.g. Bluetooth, ZigBee) and used to transfer data between personal connected devices
Keywords: Physical Layer, Network communication layer, Standard, Other cross-cutting concepts.

World Wide Web Consortium (W3C): The W3C is an international community where member organizations, a full-time staff, and the public work together to develop Web standards. W3C organize different groups. The Working Groups typically produce deliverables like standards track technical reports, software, test suites, and reviews of the deliverables of other groups, while the primary goal of the Interest Group is to bring together people who wish to evaluate potential Web technologies and policies. The Community Groups enable anyone to socialize their ideas for the Web at the W3C for possible future standardization, while the Business Groups provide companies anywhere in the world with access to the expertise and community needed to develop open Web technology [Ref 342].
Keywords: Standard, Other cross-cutting concepts.


Keywords

Abstraction Layer: The layer that provides the interfaces and the event and action management through simple rules engine to allow mapping of low level sensor events to high level events and actions, while assuring the basic analytics for data normalization, reformatting, cleansing and simple statistics. IoT systems scale corporate and global level and require multiple storage systems to accommodate IoT device data and data from traditional enterprise ERP, HRMS, CRM, and other systems. The data abstraction functions are rendering data and its storage in ways that enable developing simpler, performance-enhanced applications. Data abstraction layer processes data and reconcile multiple data formats from different sources, assuring consistent semantics of data across sources, confirming that data is complete to the higher-level application, consolidating data, providing access to multiple data stores through data virtualization, normalizing or denormalizing and indexing data to provide fast application access, protecting data with appropriate authentication and authorization.

Agrifood: This term applies to the production of food by agricultural means.

Artificial Intelligence (AI): A term used for technology devices, machines, systems) that is able to simulate human cognition (intelligence, cognitive computing) such as learning, understanding, reasoning, decision making, and interacting with other devices or humans in a complex environment. Typical applications are related to speech recognition, autonomous vehicles, transmission route optimization, quick decisions/actions based on big and complex data, or simply replacing routine work [Ref 21].

Analytics: See Data Analytics.

Applications: See Application layer.

Application layer: Application layer is offering the software platforms that are suited to deliver the key components for implementing various IoT applications that are connecting users, business partners, devices, machines, and enterprise systems with each other and the information interpretation is provided. Software at this layer interacts with the service layer, while the software applications are based on vertical markets, the nature of device data, and business needs. At this layer, many applications are addressed such as mission-critical business applications, ERP, specialized industry solutions, mobile applications, analytic applications that interpret data for business decisions, etc.

Automated Driving Systems: See Automated Driving Systems

Relating to or concerned with motor vehicles [Ref 343]

Collaboration and process layer: Enterprise systems and platform and the exchange of data among these platforms. includes people and processes. The layer addresses the processes that involves people, organisations that use applications and associated data for their specific needs or for a range of different purposes, to provide the right data, at the right time, to perform the right thing. End to end security is address for each layer and as the data is moved across the layers to secure each device or system, provide security for all processes at each level, secure end to end exchange and communication between each layer.

Data: Information represented in a manner suitable for automatic processing [Ref 344].

Framework: In general, a framework is a real or conceptual structure intended to serve as a support or guide for the building of something that expands the structure into something useful[Ref 345].

Internet of Things (IoT): IoT is “A dynamic global network infrastructure with self-configuring capabilities based on standard and interoperable communication protocols where physical and virtual “things” have identities, physical attributes, and virtual personalities and use intelligent interfaces, and are seamlessly integrated into the information network”. ITU-T has formulated the following definition: “Internet of things (IoT): A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies. Note 1: Through the exploitation of identification, data capture, processing and communication capabilities, the IoT makes full use of things to offer services to all kinds of applications, whilst ensuring that security and privacy requirements are fulfilled. Note 2: From a broader perspective, the IoT can be perceived as a vision with technological and societal implications[Ref 346][Ref 347].

Legislation: A law or set of laws suggested by a government and made official by a parliament [Ref 336].

Machine Learning (ML): Machine learning is an application of artificial intelligence (AI) that gives systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves [Ref 348][Ref 349].

Network communication layer: The role of communicating information in entirely new contexts: sensor technology enables actions in the world to give rise to data while network links allow to create and communicate. This includes transmissions between devices and the network, across networks, and between the network and low-level information processing occurring. Data communication networks have multiple functions, as described by ISO 7-layer reference model. The IoT systems contain many levels in addition to the communications network.

Other cross-cutting concepts: This keyword refers to concepts not related to any specific IoT architecture layer, or to several of them at the same time. The IoT architecture layers considered in this Handbook are, from bottom to top, Physical layer, Network communication layer, Processing layer, Storage layer, Abstraction layer, Service layer, Application layer and Collaboration and process layer.

Physical layer: The basis for all IoT technologies is the hardware, e.g. without the infrastructure (e.g. datacentres, servers, etc.) there is no cloud service. The physical layer is the first option to design IoT systems "from the ground", e.g. by integrating relevant functions already on chip level, thereby building entire systems (SOC = system on chip). Advantages of this approach are usually a high level of security and reliability. On the other hand, this approach offers only a limited amount of flexibility regarding the use cases.

Processing layer: The layer addresses the edge computing, data element analysis and transformation, analytics, mining, machine learning, pervasive considering that autonomic services are provided through ubiquitous machines in both "autonomic" and "smart" way. The processing layer convert network data flows into information that is suitable for storage and higher-level processing and provides the ability to process and act upon events created by the edge devices and store the data into a database in the storage layer. The requirements for the processing layer are connected to the need for highly scalable, columnbased data storage for storing events, map-reduce for long-running batch-oriented processing of data and complex event processing for fast in-memory processing and near real-time reaction and autonomic actions based on the data and activity of devices and the interconnected systems. Edge computing requires processing at the gateway level and the enterprise applications leverage edge devices data in end-to-end value streams involving edge devices and people within digitized processes.

Processors: A central processor, or CPU, is arguably the most important component of any computing device. It handles basic instructions and allocates the more complicated tasks to other specific chips to get them to do what they do best. It’s the core of your PC, smartphone, or tablet. and it’s what makes the whole device run as it should.[Ref 350].

Security: Property of an IT system by which confidentiality, integrity, availability, accountability, authenticity, and reliability are achieved[Ref 275].

Service layer: The layer that integrates the middleware that sits on top of networks and IoT device streams and provides data management and data analytics are vital functions in IoT systems where large amounts of sensor generated data and events must be logged, stored and processed to generate new insights or events on which business decisions can be taken.

Standard: A technical standard is an established norm or requirement in regard to technical systems. It is usually a formal document that establishes uniform engineering or technical criteria, methods, processes and practices. In addition, a custom, convention, company product, corporate standard, etc. that becomes generally accepted and dominant is often called a de facto standard[Ref 351]

Storage layer: The IoT stakeholders addressing this layer consider the efficient storage and organization of data and the continuous update of data with new information, as it made available through the capturing and processing channels. Archiving the raw and processed data addresses the offline long-term storage of data that is not needed for the IoT system's real-time operations. Centralized storage considers the deployment of storage structures that adapt to the various data types and the frequency of data capture. Relational database management systems can be used that involves the organization of data into a table schema with predefined interrelationships and metadata for efficient retrieval for later use and processing. Storage technologies such NoSQL key-value stores are used to support big data storage with no reliance on relational schema or strong consistency requirements typical of relational database systems. For autonomous IoT applications, the storage can be decentralized, and data is kept at the edge or at the objects that generate it and is not sent up the system.

Tensorflow: TensorFlow is a free and open-source software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks. It is used for both research and production at Google[Ref 352]

Wireless: The transfer of information over a distance without the use of enhanced electrical conductors or ‘wires’. The distances involved may be short (a few meters as in television remote control) or long (thousands or millions of kilometers for radio communications). When the context is clear, the term is often shortened to ‘wireless’. Wireless communication is generally considered to be a branch of telecommunications.[Ref 353].


References

  1. ITU Radiocommunication Sector. Online at: http://www.itu.int/en/ITU-R http://www.itu.int/en/ITU-R
  2. Radio Spectrum Policy Group. Online at: http://rspg-spectrum.eu/ http://rspg-spectrum.eu
  3. The 5G Infrastructure Public Private partnership. Online at: https://5g-ppp.eu/ https://5g-ppp.eu
  4. 5G Infrastructure Public Private Partnership (5G PPP). Online at: https://5g-ppp.eu/
  5. 5GUK Limited. Online at: https://5g.co.uk/guides/what-is-5g-new-radio/
  6. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  7. Business Dictionary, "Accountability". Online at: http://www.businessdictionary.com/definition/accountability.html
  8. K. Karpinska, P. Dykstra, "The Active Ageing Index and its extension to the regional level" European Union, 2015.
  9. J. H. Zheng and W. R. Tan, "An Adaptive Gateway for Smart Home". Online at: http://ieeexplore.ieee.org/document/6643370/
  10. European Commission, Advanced driver assistance systems, European Commission, Directorate General for Transport, November 2016
  11. 11.00 11.01 11.02 11.03 11.04 11.05 11.06 11.07 11.08 11.09 11.10 https://ec.europa.eu/agriculture/glossary
  12. European Commission, "Ageing Well in the Information Society" in COM, 2007.
  13. Wikipedia, "Agile software development" 10 September 2017. Online at: https://en.wikipedia.org/w/index.php?title=Agile_software_development&oldid=799886528. Accessed 13 September 2017.</nowiki>
  14. 14.0 14.1 P. Kunz. "Ambient Assisted Living" 2011. Online at: http://www.ercim.eu.
  15. D. J. Cook, J. C. Augusto and V. R. Jakkula, "Ambient intelligence: Technologies, applications, and opportunities". Online at: http://www.sciencedirect.com/science/article/pii/S157411920900025X
  16. I Can Localize. "Localization for Mobile Apps - a Refresher". Online at: https://www.icanlocalize.com/site/2013/04/localization-for-mobile-apps-a-refresher/
  17. K. GUNNARSDÓTTIR, M. ARRIBAS-AYLLON. "Ambient Intelligence: A narrative in search of users" Lancaster University and SOCSI, 2012.
  18. Alliance for Internet of Things Innovation (AIOTI). Online at: https://aioti.eu/
  19. Functional architecture, OneM2M Technical Specification (TS-001-V2.10.0), August 2016. Online at: http://www.onem2m.org/images/files/deliverables/Release2/TS-0001-%20Functional_Architecture-V2_10_0.pdf
  20. Wikipedia, "Application Programming Interface" 28 August 2017. Online at: https://en.wikipedia.org/wiki/Application_programming_interface
  21. 21.0 21.1 21.2 21.3 21.4 21.5 Gartner Inc. Online at: http://www.gartner.com/it-glossary
  22. IEEE Standard Association. "IoT Architecture - Internet of Things (IoT) Architecture" in Standard development working group.
  23. 23.00 23.01 23.02 23.03 23.04 23.05 23.06 23.07 23.08 23.09 23.10 23.11 23.12 O. Vermesan and P. Friess. "Digitising the Industry - Internet of Things Connecting the Physical, Digital and Virtual Worlds" in River Publishers, 2016.
  24. M. Bijvoet. "Art as Enquiry: Toward New Collaborations between Art, Science and Technology". Peter Lang Pub Inc., New York, 1997.
  25. L. Duxbury, E. Grierson, D. Waite. "Thinking Through Practice: Art as Research in the Academy". RMIT Publishing, 1997.
  26. 26.0 26.1 26.2 26.3 26.4 26.5 26.6 L. Girão, J.P. Valgaeren, E. Van Passel. "Activities Linking ICT and Art: Past Experience – Future Activities. A study prepared for the European Commission DG Communications Networks, Content & Technology” EU Commission Final Report, 2013. Online at: http://ec.europa.eu/newsroom/dae/document.cfm?doc_id=9122
  27. H. Borgdorff. "The Production of Knowledge in Artistic Research - The Routledge Companion to Research in the Arts". 2011.
  28. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  29. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  30. European Roadmap Smart Systems for Automated Driving Archived, 12 February 2015, European Technology Platform on Smart Systems Integration (EPoSS), 2015.
  31. S. Jeschke, I. Isenhardt, F. Hees, K. Henning. "Automation, Communication and Cybernetics in Science and Engineering", 2015/2016.
  32. G. A. CORBI, "The Tivoli software implementation of autonomic computing guidelines", IBM SYSTEMS JOURNAL, vol. 42, nº 1, 2003.
  33. Society of Automotive Engineers (SAE). Standard J3016_201806: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles. Online at: https://doi.org/10.4271/J3016_201806
  34. J. H. Brown. "From precision farming to autonomous farming: How commodity technologies enable revolutionary impact". Online at: http://robohub.org/from-precision-farming-to-autonomous-farming-how-commodity-technologies-enable-revolutionary-impact/
  35. A. Meystel, E.R. Messina. "Measuring the Performance and Intelligence of Systems: Proceedings of the 2000 PerMIS Workshop" NIST 2000.
  36. Business Dictionary, "Availability". Online at: http://www.businessdictionary.com/definition/availability.html
  37. Technopedia Definition, "Barcode". Online at: https://www.techopedia.com/definition/24410/bar-code
  38. A. F. Griffith. "Improving project system performance through benchmarking", Paper presented at PMI® Global Congress, 2006.
  39. Gartner, IT Glossary. Online at: https://www.gartner.com/it-glossary/big-data/
  40. Big Data Value Association (BDVA). Online at: http://www.bdva.eu/about
  41. https://en.wikipedia.org/wiki/Biosensor
  42. TechTarget. Online at: https://searchcio.techtarget.com/definition/blockchain
  43. A. Chabba. RESET - Digital for good. "Blue Economy! What is it?". Online at: https://en.reset.org/blog/blue-economy-what-it
  44. https://www.techopedia.com/definition/794/broadband
  45. J. F. Moore. “The Death of Competition: Leadership and Strategy in the Age of Business Ecosystems”, HarperBusiness, 1996, p. 297.
  46. A. Osterwalder, Y. Pigneur, "Business Model Generation" John Wiley & Sons, 2010.
  47. TechTarget, "B2B (business-to-business)". Online at: https://searchcio.techtarget.com/definition/B2B
  48. Investopedia, Business to Consumer - B2C. Online at: https://www.investopedia.com/terms/b/btoc.asp
  49. TechTarget, B2B2C (The Business-to-Business-to-Consumer). online at: https://whatis.techtarget.com/definition/B2B2C-business-to-business-to-consumer
  50. IoT Relation and Impact on 5G (Rel.2), AIOTI WG03 - IoT Standardisation, 2019. Online at: https://aioti.eu/aioti-wg03-reports-on-iot-standards/ The AUTOPILOT project, Final specification of communication system for IoT enhanced AD (D1.8). Online at: https://autopilot-project.eu/deliverables/
  51. ISO/IEC 17000:2004. Definition 5.5
  52. A. Murray, K. Skene, K. Haynes, "The circular economy: An interdisciplinary exploration of the concept and application in a global context" Journal of Business Ethics, vol. 140, no. 3, pp. 369-380, 2017.
  53. Y.-C. Chen. "Citizen-centric e-government services: Understanding integrated citizen service information systems" Social Science Computer Review, vol. 28, no. 4, pp. 427-442, 2010.
  54. B. P. Rao, A. Mittal, P. Saluia, S. V. Sharma, "Cloud computing for Internet of Things & sensing based applications. In Sensing Technology (ICST)" in Sixth International Conference, 2012.
  55. N. Antonopoulos, L. Gillam, "Cloud computing. London: Springer" 2010.
  56. M. Aazam, I. Khan, A. A. Alsaffar, E. N. Huh. "Cloud of Things: Integrating Internet of Things and cloud computing and the issues involved" Sciences and Technology (IBCAST), pp. 414-419, 11 January 2014.
  57. UNIFY-IoT, "Activities Fostering Value Co-creation: Interim Report" 2017.
  58. A. Shankar, H. Cherrier, R. Canniford. "Consumer empowerment: a Foucauldian interpretation" European Journal of Marketing, vol. 40, no. 9/10, pp. 1013-1030.
  59. 59.0 59.1 D. Bohm. On Creativity, 2014, CBInsights ed., Routledge Classics IoT Periodic Table, 1998.
  60. Q. Wu. "Cognitive Internet of Things: A New Paradigm beyond Connection" IEEE Journal of Internet of Things, 2014.
  61. S. Matthews. "What is cognitive IoT?" IBM Big Data & Analytics Hub, March 2016.
  62. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  63. Functional architecture, OneM2M Technical Specification (TS-001-V2.10.0), August 2016. Online at: http://www.onem2m.org/images/files/deliverables/Release2/TS-0001-%20Functional_Architecture-V2_10_0.pdf
  64. TechTarget. Online at: https://whatis.techtarget.com/definition/Computer-Security-Incident-Response-Team-CSIRT
  65. http://cyberlaw.stanford.edu/blog/2013/12/sae-levels-driving-automation
  66. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  67. A. Gunasekaran, E.W.T Ngai. "Information systems in supply chain integration and management" European Journal of Operational Research, vol. 159, no. 2, pp. 269-295, 2004.
  68. Cambridge Dictionary, "Connectivity,". Online at: http://dictionary.cambridge.org/dictionary/english/connectivity
  69. GDPR, art. 4 (11). Online at: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32016R0679&from=EN
  70. BusinessDictionary.com, "Consumer awareness" 04 September 2017. Online at: http://www.businessdictionary.com/definition/consumer-awareness.html
  71. TechTarget. Online at: https://whatis.techtarget.com/definition/context-awareness
  72. Gartner Inc. IT Glossary. Online at: https://www.gartner.com/it-glossary/context-aware-computing-2/
  73. GDPR, art. 4 (7). Online at: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32016R0679&from=EN
  74. Cyber-Physical Systems. Online at: http://cyberphysicalsystems.org/index.htm
  75. B. Mufson. "Meet the Artist Using Ritual Magic to Trap Self-Driving Cars" VICE, 2017. Online at: https://creators.vice.com/en_au/article/qkmeyd/meet-the-artist-using-ritual-magic-to-trap-self-driving-cars
  76. M. B. "Art and Design: What’s the Big Difference" Critique Magazine, 1998.
  77. D02.03 - Common methodologies and KPIs for design, testing and validation
  78. ISO/IEC 18014- 2:2009
  79. CPSoS, Online at: http://www.cpsos.eu/project/what-are-cyber-physical-systems-of-systems/
  80. https://www.audinate.com/solutions/dante-overview
  81. R. Kissel. "Glossary of key information security terms". NIST Interagency Reports NIST IR 7298.3, 2013.
  82. Y. Sun, H. Song, A. J. Jara, R. Bie. "Internet of things and big data Analytics for smart and connected communities" IEEE Access, vol. 4, pp. 766-773, 2016.
  83. P. Zikopoulos, C. Eaton. "Understanding big data: Analytics for enterprise class hadoop and streaming data" McGraw-Hill Osborne Media, 2011.
  84. [ISO/IEC 2382:2015, 2126390]
  85. [ISO 26162:2012, 3.2.3]
  86. http://www.datagovernance.com/glossary-governance/
  87. https://www.techopedia.com/definition/30604/data-governance-framework
  88. B. V. Asbroeck, J. Debussche, J. César. "Building the European Data Economy - Data Ownership" White Paper, January 2017.
  89. [ISO/TS 21719-2:2018, 3.8]
  90. IDATE DigiWorld, Connected Healthcare, June 2016.
  91. Directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data.
  92. Data Protection Act 1998, Chapter 29.
  93. ITU Terminology https://www.itu.int/net/ITU-R/asp/terminology-definition.asp?lang=en&rlink={79611D63-DCA7-4D8C-BECB-7606D9DD27CE}
  94. P. Keen. "Decision support systems: a research perspective" Center for Information Systems Research, Alfred P. Sloan School of Management., 1980. Online at: http://hdl.handle.net/1721.1/47172
  95. "Deep Learning: The Next Evolution in Programming. Presentation" Online at: https://public.dhe.ibm.com/common/ssi/ecm/lb/en/lbm12348usen/LBM12348USEN.PDF
  96. ISO/IEC 14776 372:2011, 3.1.10
  97. V. Kapadekar, S. Marolia, B. Rao. "U.S. Patent Application" vol. 11, no. 552, p. 942, 2006.
  98. Whatis.com "Digital". Online at: http://whatis.techtarget.com/definition/digital
  99. ITU Terminology https://www.itu.int/net/ITU-R/asp/terminology-definition.asp?lang=en&rlink={9A6D2644-9879-40A3-8DB3-9A33C56B5CB9}
  100. OECD, "Measuring the Digital Economy: A New Perspective" OECD Publishing, 2014.
  101. E. Futurium, "Implementing the Digitising European Industry actions" Report of WG2: Digital Industrial Platforms, Aug 2017.
  102. D. Nylén; , J. Holmström. "Digital innovation strategy: A framework for diagnosing and improving digital product and service innovation" Business Horizons, vol. 58, no. 1, pp. 57-67, 2015.
  103. M. Kenney, J. Zysman. "Choosing a future in the platform economy: the implications and consequences of digital platforms" in Kauffman Foundation New Entrepreneurial Growth Conference, 2015.
  104. EC-Council, "Computer Forensics: Investigating Network Intrusions and Cyber Crime" Nelson Education, 2009.
  105. European Commission, "Digital Single Market" Online at: https://ec.europa.eu/digital-single-market/en/shaping-digital-single-market
  106. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  107. European Commission, "Digitising European Industry - Reaping the full benefits of a Digital Single Market" in COM (2016) 180 final.
  108. European Commission, The Directive on security of network and information systems (NIS Directive). Online at: https://ec.europa.eu/digital-single-market/en/network-and-information-security-nis-directive
  109. D02.03 - Common methodologies and KPIs for design, testing and validation
  110. W. Shi, J. Cao, Q. Zhang, Y. Li, L. Xu. "Edge computing: Vision and challenges" IEEE Internet of Things Journal, vol. 3, no. 5, pp. 637-646, 2016.
  111. e-commerce (electronic commerce or EC). Online at: https://searchcio.techtarget.com/definition/e-commerce
  112. DigitalEurope, New study outlines the benefits of e-labelling scheme in Europe. Online at: http://www.digitaleurope.org/Press-Room/Latest-News/News-Story/newsID/742 Matheu-García, S.N. Risk-based automated assessment and testing for the cybersecurity certification and labelling of IoT devices. Elsevier B.V., August 2018. Online at: https://www.sciencedirect.com/science/article/pii/S092054891830137
  113. D. D. Gajski, F. Vahid, S. Narayan, J. Gong. “Specification and design of embedded systems”, vol. 4, Englewood Cliffs: Prentice Hall, 1994.
  114. J. Song, Y. X. Wang, F. Xu. "Reform of embedded system experiments teaching oriented IOT[J]" Laboratory Science, vol. 1, pp. 20-22, 2011.
  115. E. Khorov, A. Lyakhov, A. Krotov, A. Guschin. "A survey on IEEE 802.11ah: An enabling networking technology for smart cities" Online at: http://www.sciencedirect.com/science/article/pii/S0140366414002989
  116. ATIS Telecom Glossary, "End-to-end security", September 2017. Online at: http://www.expertglossary.com/definition/end-to-end-security.
  117. Recommendation ITU-R F.1499 (2000) - Definitions and abbreviations
  118. 5GUK Limited. Online at: https://5g.co.uk/guides/what-is-enhanced-mobile-broadband-embb/
  119. F. Berman, V. Cert. "Social and Ethical Behavior in the Internet of Things", Communications of the ACS Vol 60, Issue 2" 2017. Online at: https://www.forbes.com/sites/ciocentral/2016/12/21/on-the-ethical-use-of-data-vs-the-internet-of-things/%233ab9d0aa1247
  120. The European Cyber Security Organisation (ECSO), About ECSO. Online at: https://www.ecs-org.eu/
  121. European Research Cluster on the Internet of Things (IERC). Online at: http://www.internet-of-things-research.eu/
  122. The European Union Agency for Network and Information Security (ENISA). Online at: https://www.enisa.europa.eu/about-enisa
  123. K. Ashton. "That 'Internet of Things' Thing," RFID Journal, 2009.
  124. I. Ingardi, L. GirãoxI. "Building the Hyperconnected Society - IoT Research and Innovation Value Chains, Ecosystems and Markets" ERL -The Experience Readiness Level, IERC Position Paper, 2016.
  125. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  126. European Commission, Factories of the Future PPP: towards competitive EU manufacturing. Online at: http://ec.europa.eu/research/press/2013/pdf/ppp/fof_factsheet.pdf
  127. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  128. Oxford Dictionary.
  129. B. Burke. "US Federal CIO Faces a Daunting Challenge" Online at: http://blogs.gartner.com/brian_burke/2009/03/11/us-federal-cio-faces-a-daunting-challenge/
  130. F. Bonomi, R. Milito, J. Zhu, S. Addepalli. "Fog computing and its role in the internet of things" in In Proceedings of the first edition of the MCC workshop on Mobile cloud computing, ACM, August 2012.
  131. FAO, "Food Security Information for Action Food Security Concepts and Frameworks" Online at: www.fao.org/elearning/course/FC/en/word/trainerresources/learnernotes0411.doc
  132. C. N. Verdouw, J. Wolfert, A. J. M. Beulens, A. Rialland. "Virtualization of food supply chains with the internet of things" Journal of Food Engineering, vol. 176, pp. 128-136, 2016.
  133. European Union, No. 178/2002 of the European Parliament and of the Council of 28 January 2002 laying down the general principles and requirements of food law, establishing the European Food Safety Authority and laying down procedures in matters of food safety,Online at: http://data.europa.eu/eli/reg/2002/178/oj
  134. http://www.urbandataplatform.hamburg/
  135. Federal Register -The Daily Journal of the United States Government, "Federal Trade Commission" Online at: https://www.federalregister.gov/agencies/federal-trade-commission
  136. http://cyberlaw.stanford.edu/blog/2013/12/sae-levels-driving-automation
  137. Siemens. "Functional Printing - Additive production of electronics". Online at: http://w3.siemens.com/mcms/mc-solutions/en/mechanical-engineering/printing-machines/functional-printing/pages/functional-printing.aspx
  138. General Data Protection Regulation (GDPR). Online at: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32016R0679&from=EN
  139. D02.03 - Common methodologies and KPIs for design, testing and validation
  140. https://nest.com/google-home-hub/
  141. https://github.com/gost/server
  142. F. Frederix, P. Friess, O. Vermesan. "Internet of Things - IoT Governance, Privacy and Security Issues, European Research Cluster on the Internet of Things" in European Commission, Internet of Things Expert Group (E02514).
  143. https://en.wikipedia.org/wiki/Graphics_processing_unit
  144. http://cyberlaw.stanford.edu/blog/2013/12/sae-levels-driving-automation
  145. Comsol Inc, "High-Performance Computing" Online at: https://www.comsol.pt/multiphysics/high-performance-computing
  146. S. Prize and M. Hieslmair, "New Prospects Are Emerging, Ars Electronica Blog" 2016. Online at: https://www.aec.at/aeblog/en/2016/02/10/startsprize2016/
  147. D. Manceau, P. Morand. "A few arguments in favor of a holistic approach to innovation in economics and management”, Journal of Innovation Economics & Management 2014/3 (n°15)" in Council conclusions on “cultural and creative crossovers to stimulate innovation, economic sustainability and social inclusion” of the Latvian Presidency of the Council of the European Union, 2015.
  148. Heetae Yang et al., 2018. IoT Smart Home Adoption: The Importance of Proper Level Automation. Journal of Sensors, Volume 2018, Article ID 6464036, 11 pages. Online at: https://doi.org/10.1155/2018/64640
  149. R. Viola. "Staff Working Document on advancing the Internet of Things in Europe”, DSM Blogpost, Online at: http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52016SC0110
  150. E. Uhlmann. "FUTUR - Vision Innovation Realisation", Futur 1-2/2007, Fraunhofer IPK, vol. 9.
  151. "Evince Development Pvt. Ltd. Human to Machine communication" Online at: https://evincedev.com/
  152. S. Wilson. "Art + Science Now", Thames & Hudson, 2010.
  153. 153.0 153.1 153.2 O. Vermesan, P. Friess. "Building the Hyperconnected Society" - IoT Research and Innovation Value Chains, River Publishers, Ed., Ecosystems and Markets, 2015.
  154. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  155. Gartner Inc. IT Glossary. Online at: https://www.gartner.com/it-glossary/identity-and-access-management-iam/
  156. D02.03 - Common methodologies and KPIs for design, testing and validation
  157. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  158. European Network for Independent Living, Online at: http://enil.eu/
  159. 159.0 159.1 159.2 159.3 159.4 159.5 159.6 O. Vermesan, J. Bacquet. "Cognitive Hyperconnected Digital Transformation - Internet of Things Intelligence Evolution", River Publishers, 2017.
  160. i-SCOOP, "Industrial Internet of Things (IIoT): Definition, benefits, standards and evolutions" Online at: https://www.i-scoop.eu/
  161. H. Lasi, P. Fettke, H. G. Kemper, T. Feld, M. Hoffmann. "Industry 4.0. Business & Information Systems Engineering" vol. 6, no. 4, pp. 239-242, 2014.
  162. F. Shrouf, J. Ordieres, G. Miragliotta. xxI. "Smart factories in Industry 4.0: A review of the concept and of energy management approached in production based on the Internet of Things paradigm" in Industrial Engineering and Engineering Management, IEEE December 2014.
  163. T.H. Davenport, J. Short. "The new industrial engineering: information technology and business process redesign", 1990.
  164. TechTarget, "IT infrastructure". Online at: http://searchdatacenter.techtarget.com/definition/infrastructure
  165. Schumpeter. "The theory of economic development: an inquiry into profits, capital, credit, interest and the business cycle", Harvard Economic, vol. 46, Harvard College, 1934.
  166. D. S. Oh, F. Phillips, S. Park, E. Lee. xxD. "Innovation ecosystems: A critical examination" Technovation, vol. 54, pp. 1-6, 2016.
  167. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  168. 168.0 168.1 O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  169. https://www.i-scoop.eu/building-management-building-management-systems-bms/
  170. Siciliano B., Khatib O., 2008. Handbook of Robotics, Springer-Verlag Berlin Heidelberg, ISBN 978-3-540-23957-4. Duchoň F., Hubinský P., 2012. Intelligent Vehicles as the Robotic Applications. Procedia Engineering, Volume 48, 2012, Pages 105-114
  171. M. Macdonald-Wallace. "The Internet of Autonomous Things: Strong Devices, Weakly Connected", Resin.io, April 2014. Online at: https://resin.io/
  172. H.J. Appelrath, O. Terzidis, C. Weinhardt. "Internet of energy," Internet of energy. Engineering & Technology”, vol. 16, no. 5, pp. 42-45, 2012.
  173. O. Vermesan, et. al. "Internet of Energy - Connecting Energy Anywhere Anytime, in Advanced Microsystems for Automotive Applications 2011: Smart Systems for Electric, Safe and Networked Mobility", Springer 2011, pp. 33-48.
  174. Internet of Energy for Electric Mobility Project 2010. Online at www.artemis-ioe.eu
  175. TechTarget, Network, " A guide to healthcare IoT possibilities and obstacles", Online at: http://searchhealthit.techtarget.com/
  176. K. Nahrstedt. "Internet of Mobile Things: Challenges and Opportunities" PACT, 2014.
  177. 177.0 177.1 D. Kara, S. Carlaw. "The Internet of Robotics Things" ABI Research, September 2014. Online at: https://www.abiresearch.com/
  178. 178.0 178.1 i-SCOOP, "The Internet of Robotic Things (IoRT): Definition, market and examples" Online at: https://www.i-scopp.eu/
  179. Wikipedia, "Interoperability", Online at: https://en.wikipedia.org/w/index.php?title=Interoperability&oldid=794798655 . Accessed 10 August 2017.
  180. 180.0 180.1 180.2 180.3 ITU, "Internet of Things Global Standards Initiative" 26 June 2015.
  181. 181.0 181.1 181.2 181.3 181.4 J. Gubbi, R. Buyya, S. Marusic, M. Palaniswami. "Internet of Things (IoT): A vision, architectural elements, and future directions" Future generation computer systems, vol. 29, no. 7, pp. 1645-1660, 2013.
  182. IoT European Large-Scale Pilots Programme. Online at: https://european-iot-pilots.eu/
  183. "Horizon 2020 Work Programme 2016-2017: Internet Of Things Large Scale Pilots".
  184. IoT European Platform Initiative. Online at: http://iot-epi.eu
  185. https://whatis.techtarget.com/definition/IoT-gateway
  186. TechTarget, "IoT policy", Online at: http://internetofthingsagenda.techtarget.com/definition/IoT-policy-Internet-of-Things-policy
  187. Belimo, IoT Glossary
  188. 188.0 188.1 A. Banafa. "IoT Standardization and Implementation Challenges”, IEEE Internet of Things, Online at: https://iot.ieee.org/newsletter/july-2016/iot-standardization-and-implementation-challenges.html
  189. E. Darmois, L. Daniele, P. Guillemin, J. Heiles, P. Moretto; A. Van der Wees. "IoT Standards Landscape - State of the Art Analysis and Evolution", Online at: https://www.riverpublishers.com/pdf/ebook/chapter/RP_9788793609105C6.pdf
  190. Mouser Electronics, "Internet of Things", Online at: http://pt.mouser.com/applications/internet-of-things/
  191. Z. Yan, P. Zhang; Vasilakos, A.V. Vasilakos. "A survey on trust management for Internet of Things" Journal of network and computer applications, vol. 42, pp. 120-134, 2014.
  192. European Commission, "What are KETs and why are they important?" Online at: https://ec.europa.eu/growth/industry/policy/key-enabling-technologies/description_en
  193. ITU-T Y.4901 (06/2016) Overview of Key Performance Indicators
  194. Price Waterhouse Coopers (PWC), "Guide to key performance indicators" 2007. Online at: https://www.pwc.com/gx/en/audit-services/corporate-reporting/assets/pdfs/uk_kpi_guide.pdf
  195. Wikipedia. "Product liability". Online at: https://en.wikipedia.org/w/index.php?title=Product_liability&oldid=794774971 Last access: 2017 September 20
  196. ISO/IEC 15288:2008, 4.11.
  197. 197.0 197.1 LoRa Alliance. Online at: https://www.lora-alliance.org/
  198. Semtech Corporation. Online at: www.semtech.com
  199. Austrian Financial Market Authority (FMA), Glossary. Online at: https://www.fma.gv.at/en/glossary/loss-given-event-lge/
  200. Sigfox Technology, Overview, 2017. Online at: https://www.sigfox.com/en/sigfox-iot-technology-overview
  201. Evince Development, "Machine to human communication" Online at: https://evincedev.com/machine-to-human-communication
  202. G. Wu, S. Talwar, N. Himayat, K.D. Johnson. "From mobile to embedded internet", IEEE Communications Magazine vol. 49, no. 4.
  203. Manufacturing Readiness Level (MRL) Deskbook. Online at: http://www.dodmrl.com/MRL_Deskbook_2017.pdf
  204. A. Arora, A. Fosfuri, A. Gambardella. "Markets for technology in the knowledge economy", ISSN 0020-8701 - International Social Science Journal, March 2002.
  205. The Economist, "Mass Customisation" Online at: http://www.economist.com/node/14299807
  206. B. J. Pine, J. H. Gilmore. "The Four Faces of Mass Customisation" Harvard Business Review, January-February- 1997.
  207. 5GUK Limited. Online at: https://5g.co.uk/guides/what-is-enhanced-mobile-broadband-embb/
  208. Q. Mahmoud. "Middleware for Communications", John Wiley&Sons Ltd., 2005, p. 522.
  209. Radio-Electronics.com"What is MIMO? Multiple Input Multiple Output Tutorial". Online at: http://www.radio-electronics.com/info/antennas/mimo/multiple-input-multiple-output-technology-tutorial.php
  210. M. Patel. "Mobile Edge Computing - Introductory Technical White Paper" ETSI, September 2014.
  211. Wikipedia, Mobility as a Service. Online at: https://en.wikipedia.org/wiki/Mobility_as_a_service The AUTOPILOT project, IoT policy framework for autonomous vehicles applications (D5.4). Online at: https://autopilot-project.eu/deliverables/
  212. R. Ratasuk, B. Vejlgaard, N. Mangalvedhe, A. Ghosh. "NB-IoT system for M2M communication. In Wireless Communications and Networking Conference" in (WCNC), April 2016.
  213. 3GPP staff, "Standardization of NB-IoT completed", 3gpp.org, 2016.
  214. G.G. Chowdhury, "Natural language processing" Annual review of information science and technology, vol. 37, no. 1, pp. 51-89, 2003.
  215. NFC Forum website, NFC Forum. Online at:https://nfc-forum.org/
  216. B. M. "What is Computer Networking?”; Lifewire Online at: https://www.lifewire.com/what-is-computer-networking-816249
  217. TechTarget, "network functions virtualization (NFV)" Online at: http://searchsdn.techtarget.com/definition/network-functions-virtualization-NFV
  218. B. Gowan. "What is Network Function Virtualization (NFV)?". Ciena, 14 March 2016. Online at: http://www.ciena.com/insights/articles/What-is-NFV-prx.html
  219. C. Stergiu, D. Siganos. "Neural Networks" Online at: https://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html# What is a Neural Network https://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html# What%20is%20a %20Neural%20Network
  220. ETSI, "Next Generation Networks" Online at: http://www.etsi.org/technologies-clusters/technologies/past-work/next-generation-networks
  221. https://www.opengeospatial.org/standards/sensorthings
  222. http://forge.fiware.org/plugins/mediawiki/wiki/fiware/index.php/OMA_NGSI_10
  223. OneM2M. Online at: http://www.onem2m.org/ oneM2M Technical Specification. Functional Architecture, TS-0001-V2.10.0, 30-08-2016. Online at: http://www.onem2m.org/images/files/deliverables/Release2/TS-0001-%20Functional_Architecture-V2_10_0.pdf
  224. Open Data International. Open Data Handbook. Online at: http://opendatahandbook.org/
  225. EU Open Data Portal. Online at: http://data.europa.eu/euodp/en/about
  226. Open & Agile Smart Cities (OASC). Online at: https://oascities.org/
  227. Levine, Sheen S., & Prietula, M. J. (2013). Open Collaboration for Innovation: Principles and Performance. Organization Science, doi:10.1287/orsc.2013.0872
  228. IoT European Platforms Initiative (IoT-EPI). Advancing IoT Platforms Interoperability, River Publishers 2018. Online at: https://iot-epi.eu/wp-content/uploads/2018/07/Advancing-IoT-Platform-Interoperability-2018-IoT-EPI.pdf
  229. Vocabulary.com, "Paradigm", Online at: https://www.vocabulary.com/dictionary/paradigm
  230. GDPR, art 4 (1). Online at: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32016R0679&from=EN
  231. GDPR, art. 4 (12). Online at: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32016R0679&from=EN
  232. C. Celis-Morales, K. M Livingstone, C.F. Marsaux. "Effect of personalized nutrition on health-related behaviour change: evidence from the Food4me European randomized controlled trial”, International Journal of Epidemiology - 2016. Online at: www.food4me.org
  233. Vocabulary.com "Pervasive", Online at: https://www.vocabulary.com/dictionary/pervasive
  234. Foldoc. "Platform", Online at: https://foldoc.org/platform
  235. M. Borrus, and J. Stowsky. "Technology Policy and Economic Growth". UC Berkeley: Berkeley Roundtable on the International Economy, 1997.
  236. TechTarget, "IoT policy (Internet of Things policy)" Online at: http://internetofthingsagenda.techtarget.com/definition/IoT-policy-Internet-of-Things-policy
  237. European Parliament, "Precision agriculture – An opportunity for EU farmers - Potential support with the CAP 2014-2020" 2014.
  238. OECD, "Environmental Indicators for Agriculture Vol. 3: Methods and Results" 2011.
  239. R. V. Duarte. "1 SCR 30, 1990 CanLII 150 (SCC)" 1990.
  240. Merriam-webster. "Printed circuit". Online at: https://www.merriam-webster.com/dictionary/printed circuit
  241. "Official Journal of the European Union, L 119", 2016.
  242. ENISA, "Privacy-by-design in Big Data: An overview of privacy enhancing technologies in the era of big data Analytics" in DOI:10.2824/641480; ENISA, 2014, Privacy and Data Protection by Design – from policy to engineering, DOI: 10.2824/38623, 2015.
  243. E. C. Fitch. "Proactive Maintenance for Mechanical Systems". Elsevier, 2013.
  244. GDPR, art. 4 (2). Online at: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32016R0679&from=EN
  245. Business Dictionary. "production system", Online at: http://www.businessdictionary.com/definition/production-system.html
  246. Cambridge Dictionary, "Programme", Online at: http://dictionary.cambridge.org/dictionary/english/programme
  247. GDPR, art. 4 (4). Online at: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32016R0679&from=EN
  248. A. Shankar, B. Cova, R. Kozinets. "Consumer Tribes", Routledge, 2012.
  249. D. Tapscott, A. D. Williams. "How Mass Collaboration Changes Everything Ritzer", Wikinomics. Online at: http://abs.sagepub.com/content/56/4/379.full.pdf+html
  250. C.K. Prahalad, V. Ramaswamy. "'Co-Creation Experiences: The Next Practice in Value Creation", Journal of Interactive Marketing, vol. 18, no. 3, 2004.
  251. A. Toffler. The Third Wave, Bantam Books‎, 1980.
  252. ENISA, Public Private Partnerships (PPP) Cooperative models. ISBN 978-92-9204-241-7, DOI 10.2824/076734. November 2017. Online at: https://www.enisa.europa.eu/publications/public-private-partnerships-ppp-cooperative-models European Commission, Public Private Partnerships in research. Online at: http://ec.europa.eu/research/industrial_technologies/ppp-in-research_en.html
  253. Denso Wave Incorporated, QR Code Essentials, Denso ADC, 2011.
  254. Gartner Inc. IT Glossary. Online at: https://www.gartner.com/it-glossary/quantum-computing/
  255. K. Schweichhart. "Reference Architectural Model Industrie 4.0 (RAMI 4.0) (Presentation)" Online at: https://ec.europa.eu/futurium/en/system/files/ged/a2-schweichhart-reference_architectural_model_industrie_4.0_rami_4.0.pdf
  256. E. Batella. "Monetizacion de patentes y mercados de patentes". Centre de Patents (UB), 8 October 2012. Online at: http://www.ub.edu/centredepatents/pdf/doc_dilluns_CP/ Batalla_Monetizacion_mercados_patentes.pdf
  257. ITU. "Next Generation Networks - Frameworks and functional architecture models - Common requirements of the Internet of things". ITU-T TY.2066, 06/2014.
  258. European Union Regulations, "EUR-Lex - l14522 - EN".
  259. R.S. Khemani, D.M. Shapiro. "Glossary of Industrial Organisation Economics and Competition Law" 1993.
  260. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  261. Business Dictionary, "Research". Online at: http://www.businessdictionary.com/definition/research.html
  262. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  263. https://www.w3.org/2013/data/
  264. H.T. Mouftah, B. Kantarci. "Communication Infrastructures for Cloud Computing", IGI Global, 2013, p. 538.
  265. K. Finkenzeller. RFID handbook: “Fundamentals and applications in contactless smart cards, radio frequency identification and near-field communication”, John Wiley & Sons, 2010.
    1. X. Jia, Q. Feng, T. Fan, Q. Lei. "RFID technology and its applications in Internet of Things (IoT)", In Consumer Electronics, Communications and Networks (CECNet), in 2nd International Conference. IEEE, April 2012.
  266. X. Jia, Q. Feng, T. Fan, Q. Lei. "RFID technology and its applications in Internet of Things (IoT)", In Consumer Electronics, Communications and Networks (CECNet), in 2nd International Conference. IEEE, April 2012.
  267. ISO/IEC TR 13335-1:1996.
  268. J. Wall. "Robotics", Creative Teaching Press, p. 24, 2003.
  269. IGI Global. Online at: https://www.igi-global.com/dictionary/wireless-networks-vehicular-support/37000
  270. https://www.techopedia.com/definition/9269/scalability
  271. ISO/IEC TR 27019:2013-07-15
  272. https://www.techopedia.com/definition/13259/seamless-integration
  273. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  274. The AUTOPILOT project, IoT policy framework for autonomous vehicles applications (D5.4). Online at: https://autopilot-project.eu/deliverables/ ISO/IEC 27002:2013 Information technology -- Security techniques -- Code of practice for information security controls. Second edition, 2013-10-01. Online at: https://www.iso.org/standard/54533.html
  275. 275.0 275.1 ISO/IEC TR 15443-1:2012-11-15.
  276. IoT European Platforms Initiative (IoT-EPI). Advancing IoT Platforms Interoperability, River Publishers 2018. Online at: https://iot-epi.eu/wp-content/uploads/2018/07/Advancing-IoT-Platform-Interoperability-2018-IoT-EPI.pd
  277. D. Ghosh, R. Sharman, H.R. Rao, S. Upadhyaya. "Decision Support Systems", vol. 42, nº 4, pp. 2164-2185, January 2007. 
  278. J. Gausemeier, D. Zimmer, U. Frank, S. Pook, A. Schmidt "Conceptual design of self-optimizing systems exemplified by a magnetic linear drive". INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN, ICED’07, Cite das Sciences et L’Industrie, Paris, 2007.
  279. E. Yuan, S. Malek. "A taxonomy and survey of self-protecting software systems", SEAMS '12 Proceedings of the 7th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Zurich, 2012. 
  280. 280.0 280.1 Recommendation ITU-R M.1224 Vocabulary of terms for International Mobile Telecommunications (IMT)
  281. European Commission, "Growing the European Silver Economy (Background Paper)" February 2015. Online at: http://ec.europa.eu/research/innovation-union/pdf/active-healthy-ageing/silvereco.pdf
  282. J. Sinopoli. "Advanced Technology for Smart Buildings", Artech House, 2016, p. 222.
  283. A. Cocchia. "Smart and digital city: A systematic literature review" Springer International Publishing, pp. 13-43
  284. A. Marcus, "Design, User Experience, and Usability: Novel User Experience", 5th International Conference, DUXU 2016, Held as Part of HCI International, Toronto, 2016.
  285. B.V. Mathiesen. "Smart Energy systems for largescale renewable energy integration - How can electricity grids and district heating systems be optimised in an integrated way?", European Commission Conference: Technology Challenges and Regional Approaches for Integrating Renewables and Energy Security, May 2015. Online at: https://ec.europa.eu/energy/sites/ener/files/documents/1.4 20150527_EU_Integrated%25 20energy systems_Brian_Vad_Mathiesen.pdf
  286. N. Winters K. Walker, G. Roussos. "Facilitating learning in an intelligent environment", London Knowledge Lab, UK, 2005.
  287. A. Satyam, I. Calzada. "The Smart City Transformations: The Revolution of the 21st Century", Bloomsbury Publishing, 2017, p. 322.
  288. 288.0 288.1 Wikipedia. Online at: https://en.wikipedia.org/wiki/State_of_the_art
  289. Blue Stream Consultancy, "Smart healthcare". Online at: http://bluestream.sg/smart-healthcare
  290. C. Bühler, H. Knops. "Assistive Technology on the Threshold of the New Millennium", IOS Press, p. 832, 1999.
  291. J. Zhou, G. Salvendy. "Human Aspects of IT for the Aged Population, Healthy and Active Aging". Second international Conference, ITAP, 2016. Held as Part of HCI International 2016, Toronto.
  292. M. Weiser, R. Gold, J.S. Brown. "The origins of ubiquitous computing research at PARC in the late 1980s", IBM 1999. 
  293. J. Davis, T. Edgar, J. Porter, J. Bernarden, M. Sarli. "Smart manufacturing, manufacturing intelligence and demand-dynamic performance" Computers & Chemical Engineering, no. 47, pp. 145-156, 2012.
  294. Blue Stream Consultancy, "Smart transportation". Online at: http://bluestream.sg/smart-transportation
  295. J.-P. Vasseur, A. Dunkels. "Interconnecting Smart Objects with IP: The Next Internet", MK, 2010, p. 432.
  296. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/process-and-operations/us-cons-smart-sensors.pdf
  297. https://en.wikipedia.org/wiki/Smartwatch
  298. ISO/IEC TR 27019:2013-07-15
  299. 299.0 299.1 BEPA Report, "Social Innovation. A Decade of Changes”, ISBN 978-92-79-39417-1, 2014.
  300. S. Racherla, D. Cain, S. Irwin, P. Ljungstrøm, P. Patil, A.M. Tarenzio. "Implementing IBM Software Defined Network for Virtual Environments", IBM Redbooks, 2014, p. 248.
  301. Wikipedia, Standards organization. Online at: https://en.wikipedia.org/wiki/Standards_organization
  302. "ICT & Art - the STARTS platform", Online at: https://ec.europa.eu/digital-single-market/ict-art-starts-platform
  303. Water JPI. Online at: http://www.waterjpi.eu/mapping-agenda/strategic-research-and-innovation-agenda-sria
  304. Wikipedia, Supply-chain management. Online at: https://en.wikipedia.org/wiki/Supply-chain_management APICS Dictionary. Online at: http://www.apics.org/apics-for-individuals/publications-and-research/apics-dictionary
  305. IoT European Platforms Initiative (IoT-EPI). Advancing IoT Platforms Interoperability, River Publishers 2018. Online at: https://iot-epi.eu/wp-content/uploads/2018/07/Advancing-IoT-Platform-Interoperability-2018-IoT-EPI.pd
  306. ISO/IEC TR 15443-1:2012-11-15.
  307. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  308. IoT European Platforms Initiative (IoT-EPI). Advancing IoT Platforms Interoperability, River Publishers 2018. Online at: https://iot-epi.eu/wp-content/uploads/2018/07/Advancing-IoT-Platform-Interoperability-2018-IoT-EPI.pd
  309. K. Ramey. "What is technology – meaning of technology and its use", Use of Technology 2013. Online at: https://www.useoftechnology.com/what-is-technology/
  310. European Commission, "HORIZON 2020. Work Programme 2016-2017" 2015. Online at: http://ec.europa.eu/research/participants/data/ref/h2020/other/wp/2016_2017/annexes/h2020-wp1617-annex-g-trl_en.pdf
  311. https://www.tensorflow.org/lite
  312. FYICenter. "What is Test Bed?". Online at: http://sqa.fyicenter.com/FAQ/Software-QA-Testing/What_is_Test_Bed_.html
  313. M. Rouse. "The Developer’s Guide to IoT", TechTarget. Online at: http://internetofthingsagenda.techtarget.com/definition/Internet-of-Things-IoT
  314. Gogle's Tensor Processing Unit explained: this is what the future of computing looks like
  315. R. Ascott. "Telematic Embrace Visionary Theories of Art, Technology, and Consciousness" University of California Press, 2007.
  316. https://machinelearningmastery.com/transfer-learning-for-deep-learning/
  317. 317.0 317.1 http://5gaa.org/wp-content/uploads/2017/12/5GAA-Road-safety-FINAL2017-12-05.pdf https://en.wikipedia.org/wiki/Vehicle-to-device
  318. The Linux Information Project, "Network transparency definition".http://www.linfo.org/network_transparency.html
  319. ISO/IEC 10181-1, 3.3.28
  320. M. Blaze. "Using the KeyNote Trust Management System", 1999. 
  321. European Commission, "Digital Single Market - Digitising European Industry Questions & Answers", Brussels, 2016.
  322. Y. Yuan, X. Wu, Y. Lu. "Trustworthy Computing and Services: International Conference", ISCTCS 2013, Beijing, China, 2014. 
  323. 5GUK Limited. Online at: https://5g.co.uk/guides/what-is-enhanced-mobile-broadband-embb/
  324. Food and Agriculture Organization of the United Nations. (FAO). Online at: http://www.fao.org/urban-agriculture/en/
  325. The AUTOPILOT project, IoT policy framework for autonomous vehicles applications (D5.4). Online at: https://autopilot-project.eu/deliverables/
  326. Financial Times Lexicon. Online at: http://lexicon.ft.com/
  327. C. M. Christensen, R. S. Rosenbloom. "Explaining the attacker's advantage: Technological paradigms, organizational dynamics, and the value network" Research policy, vol. 24, no. 2, pp. 233-257, 1995.
  328. 328.0 328.1 328.2 328.3 328.4 328.5 328.6 The AUTOPILOT project, Final specification of communication system for IoT enhanced AD (D1.8). Online at: https://autopilot-project.eu/deliverables/
  329. http://5gaa.org/wp-content/uploads/2017/12/5GAA-Road-safety-FINAL2017-12-05.pdf https://en.wikipedia.org/wiki/Vehicle-to-everything
  330. http://5gaa.org/wp-content/uploads/2017/12/5GAA-Road-safety-FINAL2017-12-05.pdf https://whatis.techtarget.com/definition/vehicle-to-infrastructure-V2I-or-V2X
  331. 331.0 331.1 https://www.w3.org/
  332. The AUTOPILOT project, IoT policy framework for autonomous vehicles applications (D5.4). Online at: https://autopilot-project.eu/deliverables/
  333. O. Vermesan and J. Bacquet, Eds., Next Generation Internet of Things - Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation. ISBN: 978-87-7022-007-1 (Ebook). River Publishers 2018. Online at: Online at: https://european-iot-pilots.eu/wp-content/uploads/2018/11/Next_Generation_Internet_of_Things_Distributed_Intelligence_at_the_Edge_IERC_2018_Cluster_eBook_978-87-7022-007-1_P_Web.pdf
  334. ISO/IEC 27032:2012-07-15
  335. V.G. Bharath, R. Patil. "Virtual Manufacturing: A Review". IJERT, Conference Proceedings, NCERAME-2015.
  336. 336.0 336.1 Cambridge Dictionary.
  337. EC Mobility and Transport, ITS & Vulnerable Road Users. Online at: https://ec.europa.eu/transport/themes/its/road/action_plan/its_and_vulnerable_road_users_en
  338. https://www.w3.org/WAI/standards-guidelines/wcag/
  339. Techopedia, Web of Things (WoT). Online at: https://www.techopedia.com/definition/26834/web-of-things-wot World Wide Web Consortium (W3C). Online at: http://www.w3.org/WoT/
  340. T. O. Donovan, "A context aware wireless body area network (BAN)" in Pervasive Computing Technologies for Healthcare, 2009. PervasiveHealth 2009. 3rd International Conference on. , 2009.
  341. B. J. Smith. "WHO Health Promotion Glossary: New Terms" 2006.
  342. World Wide Web Consortium (W3C). Online at: http://www.w3.org/
  343. English Oxford Living Dictionaries: https://en.oxforddictionaries.com/definition/automotive
  344. Ref [ITU-R V.662-3 (2000) - Ap. 2 (1.12); IEV ref 701-01-11]
  345. TechTarget, WhatIs, "Framework" Online at: http://whatis.techtarget.com/definition/framework
  346. IERC, "European Research Cluster on the Internet of Things" Online at: http://www.internet-of-things-research.eu/about_iot.htm
  347. ITU-T Recommendation, Y.2060, "Overview of the Internet of things", June 2012.
  348. A. Muñoz. "Machine Learning and Optimization" March 2016. Available: https://www. cims. nyu. edu/~ munoz/files/ml_optimization.pdf
  349. A. Samuel. "Field of study that gives computers the ability to learn without being explicitly programmed".
  350. What is a CPU? https://www.digitaltrends.com/computing/what-is-a-cpu/
  351. Wikipedia, "Technical standard" 15 September 2017. Online at: https://en.wikipedia.org/w/index.php?title=Technical_standard&oldid=797024528
  352. Tensorflow, From Wikipedia, the free encyclopedia: https://en.wikipedia.org/wiki/TensorFlow
  353. Belimo, IoT Glossary