Difference between revisions of "Environmental Dress 2.0"

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== Environmental Dress 2.0 ==
== Case Study: Environmental Dress 2.0 ==
By: '''Maria Castellanos & Alberto Valverde''' <br>
By: '''Maria Castellanos & Alberto Valverde''' <br>

Latest revision as of 11:15, 6 August 2018

Case Study: Environmental Dress 2.0

By: Maria Castellanos & Alberto Valverde
as Uh513


video link

Description of Work

Environment Dress is a piece of smart clothing that uses a number of sensors to measure the aggressiveness of our surrounding environs, detecting environmental variables and alerting us to them. Our body’s natural sensors are unable to measure and anticipate factors such as an increase in ultraviolet radiation, dust or noise, and others. The interface geo-locates environmental analyses and allows users to register their mood through a smartphone app.

In consequence, we can establish the relationship between both variables and determine whether an increase in ultraviolet radiation can make the person who wears the dress feel better or whether an increase in noise level can make him or her feel more uncomfortable in a certain place. Finally, all these data are shown on an emotional map, pinpointing the most pleasant and unpleasant areas in a city.

For this show, a number of measurements were taken during a stroll around Gijón. The screen displays the changes in the environmental variables registered by the dress sensors, and the mood of the wearer of the interface, stored on the phone app; while the itinerary followed is shown on a map.

Artist Statement

We are surrounded by polluting agents and other factors that have a direct impact on our everyday lives, our mood and, ultimately, on our behaviour. Variations in noise, temperature, atmospheric pressure, ultraviolet radiation or amounts of carbon monoxide are some of the challenges we have to face on a daily basis. At the end of the day, they are agents that influence our temper and our behaviour with others.


""Environment Dress 2.0"" consists of garments that collect information about the wearer’s immediate surroundings, visualize the data and make them available via an app. Sensors collect data on: Noise, temperature, air pressure, ultraviolet radiation, carbon monoxide level.


Making available sensor output in a creative visual manner alerts the wearer and the spectator to environmental variables in an engaging manner. Sharing data in this way, encouraging emotional engagement through visualisation and feedback, has significant implications around how wearable technology and smart city infrastructure can work with citizens to enhance urban life.

Relevant LSP projects:
MONICA (Management Of Networked IoT Wearables – Very Large Scale Demonstration of Cultural Societal)
SynchroniCity (SynchroniCity: Delivering an IoT enabled Digital Single Market for Europe and Beyond)