The Deployment of a LoRaWAN-Based IoT Air Quality Sensor Network for Public Good

Abstract

The goals of this project are to implement a LoRaWAN-based network of air quality sensors in Charlottesville and to use its data to generate a comparative spatial model of air quality before and during the COVID-19 outbreak. The implementation of this network required the distribution of 'The Things Network' (TTN) LoRa gateways and our own custom-made sensor kits to volunteers distributed throughout the city. Our sensor kits measure temperature, humidity, CO2, and Particulate Matter (PM) 2.5 and 10, allowing us to take measurements in line with the EPA's air quality index as well as to keep up with modern trends in research showing the importance of CO2 as an air quality metric. Preliminary spatial analysis comparing air quality before and after March 11, 2020, the day that UVA announced all classes would move online, shows a near universal decline in carbon dioxide levels, but inconclusive changes in particulate matter.