Approximately 91% of the world population lives in environments that do not currently meet air quality standards. In the United States (U.S.), the Clean Air Act of 1970 has resulted in air pollution concentrations dropping below national standards, meaning that most communities in the U.S. have cleaner air. However, clean air is not realized across all communities, especially in communities of color, where air quality can differ significantly. Further, regulatory air quality sensors that are sparsely deployed may not accurately detect the quality of air that residents breathe in their communities. With the availability of low-cost sensors and advancement of low-cost single-board computers and microcontrollers, this research aims to provide residents with an ability to accurately understand their air quality through the deployment of an Internet of Things (IoT) air quality sensor. We will meet with residents that have been affected by both redlining and nearby pollution sources to better understand how air quality affects their daily lives and what air quality information is most beneficial to them. In addition, the team will closely collaborate with partner school(s) to create K-12 curriculum for students to learn how to create their own air quality sensor, deploy it at their school, and make the air quality readings publicly available.

In this research, we will combine the availability of low-cost particulate matter sensors with the accessibility of IoT compatible single-board computers and microcontrollers to enable publicly available fine-grained air quality information. To provide real-time access to the data, a prototype mobile application for both iOS and Android, along with a web dashboard, will be developed. To address common challenges of both power and connectivity, we will partner with PCs for People to deploy the sensors and provide connectivity through their existing infrastructure. An enclosure will be developed that ensures proper airflow, has low interference with wireless communication, and is modular to allow other sensing capabilities in the future. We will compare the findings from a test deployment of the sensors with regulatory sensors readings and share the results with the community and local officials. To ensure the sustainability of the project and provide an opportunity for it to expand, we will create an open-source Computer Science and Engineering curriculum in partnership with a local middle school and we will pilot a tech camp at our university.