Smell Pittsburgh

Author:

Hsu Yen-Chia1,Cross Jennifer2,Dille Paul1,Tasota Michael1,Dias Beatrice1,Sargent Randy1,Huang Ting-Hao (Kenneth)3,Nourbakhsh Illah1

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA, USA

2. Tufts University, Medford, MA, USA

3. Pennsylvania State University, State College, PA, USA

Abstract

Urban air pollution has been linked to various human health concerns, 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. We also applied regression analysis to identify statistically significant effects of push notifications on user engagement. 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. All citizen-contributed smell data are publicly accessible and can be downloaded from https://smellpgh.org .

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

Reference149 articles.

1. The CMU CREATE Lab. 2018. A tool for predicting and interpreting smell data obtained from Smell Pittsburgh. Retrieved from https://github.com/CMU-CREATE-Lab/smell-pittsburgh-prediction. The CMU CREATE Lab. 2018. A tool for predicting and interpreting smell data obtained from Smell Pittsburgh. Retrieved from https://github.com/CMU-CREATE-Lab/smell-pittsburgh-prediction.

2. The CMU CREATE Lab. 2018. Smell Pittsburgh. Retrieved from http://smellpgh.org/. The CMU CREATE Lab. 2018. Smell Pittsburgh. Retrieved from http://smellpgh.org/.

3. ACCAN. 2018. Allegheny County Clean Air Now. Retrieved from http://accan.org/. ACCAN. 2018. Allegheny County Clean Air Now. Retrieved from http://accan.org/.

4. American Lung Association. 2017. State of the Air. Retrieved from http://www.lung.org/our-initiatives/healthy-air/sota/. American Lung Association. 2017. State of the Air. Retrieved from http://www.lung.org/our-initiatives/healthy-air/sota/.

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