Smell Pittsburgh: Community-Empowered Mobile Smell Reporting System

TL;DR

This paper presents Smell Pittsburgh, a community-driven mobile system for reporting odors, visualizing pollution, and predicting smell events to empower residents and improve local air quality awareness.

Contribution

It introduces a novel community-empowered platform for odor reporting, visualization, and prediction, integrating public input with air quality data for urban pollution management.

Findings

Community reports helped identify pollution hotspots.

The prediction model accurately forecasted smell events.

Engagement increased community awareness and advocacy.

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.