Smell Pittsburgh: Community-Empowered Mobile Smell Reporting System
October 25, 2018 Β· Declared Dead Β· π International Conference on Intelligent User Interfaces
"No code URL or promise found in abstract"
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Authors
Yen-Chia Hsu, Jennifer Cross, Paul Dille, Michael Tasota, Beatrice Dias, Randy Sargent, Ting-Hao 'Kenneth' Huang, Illah Nourbakhsh
arXiv ID
1810.11143
Category
cs.HC: Human-Computer Interaction
Citations
35
Venue
International Conference on Intelligent User Interfaces
Last Checked
3 months ago
Abstract
Urban air pollution has been linked to various human health considerations, including cardiopulmonary diseases. Communities who suffer from poor air quality often rely on experts to identify pollution sources due to the lack of accessible tools. Taking this into account, we developed Smell Pittsburgh, a system that enables community members to report odors and track where these odors are frequently concentrated. All smell report data are publicly accessible online. These reports are also sent to the local health department and visualized on a map along with air quality data from monitoring stations. This visualization provides a comprehensive overview of the local pollution landscape. Additionally, with these reports and air quality data, we developed a model to predict upcoming smell events and send push notifications to inform communities. Our evaluation of this system demonstrates that engaging residents in documenting their experiences with pollution odors can help identify local air pollution patterns, and can empower communities to advocate for better air quality.
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