/Community-Empowered Air Quality Monitoring System

Community-Empowered Air Quality Monitoring System

Yen-Chia Hsu, Paul Dille, Jennifer Cross, Beatrice Dias, Randy Sargent and Illah Nourbakhsh
Conference Paper, Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, pp. 1607-1619, May, 2017

Download Publication (PDF)

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.


Developing information technology to democratize scientific knowledge and support citizen empowerment is a challenging task. In our case, a local community suffered from air pollution caused by industrial activity. The residents lacked the technological fluency to gather and curate diverse scientific data to advocate for regulatory change. We collaborated with the community in developing an air quality monitoring system which integrated heterogeneous data over a large spatial and temporal scale. The system afforded strong scientific evidence by using animated smoke images, air quality data, crowdsourced smell reports, and wind data. In our evaluation, we report patterns of sharing smoke images among stakeholders. Our survey study shows that the scientific knowledge provided by the system encourages agonistic discussions with regulators, empowers the community to support policy making, and rebalances the power relationship between stakeholders.

Associated Lab - CREATE: Community Robotics, Associated Lab - Education and Technology Empowerment

BibTeX Reference
author = {Yen-Chia Hsu and Paul Dille and Jennifer Cross and Beatrice Dias and Randy Sargent and Illah Nourbakhsh},
title = {Community-Empowered Air Quality Monitoring System},
booktitle = {Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems},
year = {2017},
month = {May},
pages = {1607-1619},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {dversarial design, air quality, citizen science, community engagement, data visualization, participatory design, sustainable hci},