HomeCase StudyWear AQ

Wear AQ

Environmental challenge(s) met
Air Quality
Open Data Platform

United Kingdom


Outline of project:
Wear AQ was a research project carried out by Umbrellium to assess people's subjective perception of their environment using wearable technology and machine learning algorithms to investigate personal agency and responsibility in air quality issues.

In 2017 Umbreillium worked with children from a London School in Tower Hamlets to trial out a prototype of wearable technology - Wear AQ. By going out into the School's surrounding neighborhood Wear AQ allowed the children to measure air quality both technologically, and through their own perceptions, recording their subjective experience using low tech wearable devices that catalogued their gestures. The data recorded from this excursion was then compared with the results from other more developed technologies and analysed considering other environmental parameters (i.e. temperature, wind, humidity).

The results from the analysis demonstrated that the machine learning model was able to accurately predict the children's' perception data. However, this also confirmed that location played a significant role on the children's perception of air quality, meaning that other environmental factors such as traffic, wind, and other visual cues had an impact on their perception. Moving forward, Umbrellium will now look to connect Wear AQ to IOT networks in order to enhance the machine learning model.

What stage is the project at?
Research and Development

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