Low-Cost Air Quality Sensor Networks
This project is part of an NSF-funded REU site with the HMC Computer Science Department. Applications for this project will be processed on the ETAP website. Please submit your application there and not on the URO website! Note that due to the funding source, this project is restricted to US citizens or permanent residents.
Atmospheric aerosols contribute to a variety of health concerns, including cardiovascular and respiratory conditions. In California, as in other places, that health burden falls largely on low-income communities of color. Funding is available to help qualifying communities improve their air quality, but the measurements needed to demonstrate a community’s ambient air quality has traditionally required expensive research-grade equipment. More recently, low cost sensors have provided a promising avenue for generating more spatially resolved air quality data, and advances in data processing offer hope that intelligent systems might be able to extract high-quality signals from noisy signals. This project will expand on existing work at Harvey Mudd to better understand and characterize the limits of those low cost sensors in a variety of conditions through field data collection and analysis.
This project represents a real-world, community-facing, interdisciplinary collaboration. Our work will be a mix of hands on building, field work, and data analysis. We'll build on previous work in CS and in chemistry. And most of all, we'll have fun!