Enviro-IoT: Calibrating Low-Cost Environmental Sensors in Urban Settings
Thomas Johnson, Kieran Woodward
TL;DR
Enviro-IoT presents a Raspberry Pi 4–based, low-cost air quality sensing node designed for real-time, urban deployment and calibration against DEFRA's AURN. In a 9-month co-location in Nottingham, the system achieved high agreement with reference measurements for PM2.5, PM10 and NO2, demonstrating the viability of affordable IoT-enabled monitoring. With roughly £250 per station and a 57,120-sample dataset, the work shows that scalable, real-time air quality data can be gathered in urban settings, despite connectivity challenges that were mitigated by a 4G link. The paper argues that this approach can democratize environmental monitoring and informs future expansion to additional pollutants and locations.
Abstract
Low-cost miniaturised sensors offer significant advantage to monitor the environment in real-time and accurately. The area of air quality monitoring has attracted much attention in recent years because of the increasing impacts on the environment and more personally to human health and mental wellbeing. Rapid growth in sensors and Internet of Things (IoT) technologies is paving the way for low-cost systems to transform global monitoring of air quality. Drawing on 4 years of development work, in this paper we outline the design, implementation and analysis of \textit{Enviro-IoT} as a step forward to monitoring air quality levels within urban environments by means of a low-cost sensing system. An in-the-wild study for 9-months was performed to evaluate the Enviro-IoT system against industry standard equipment is performed with accuracy for measuring Particulate Matter 2.5, 10 and Nitrogen Dioxide achieving 98\%, 97\% and 97\% respectively. The results in this case study are made up Of 57, 120 which highlight that it is possible to take advantage of low-cost sensors coupled with IoT technologies to validate the Enviro-IoT device against research-grade industrial instruments.