Mobile monitoring of air pollution using low cost sensors to visualize spatio-temporal variation of pollutants at urban hotspots

Abstract

This paper deals with the development of a smart personal air quality monitoring system (SPAMS) for real time air quality monitoring. The commercially available low-cost CO, NO$_2$, O$_3$, PM, temperature (T) and humidity (RH) sensors along with the microcontroller and GPRS were integrated in SPAMS. The developed SPAMS was calibrated in the laboratory and vali- dated through field measurements. Field measurements were performed by walking on footpaths and travelling in the bus during various times of a day and different days in a week at selected locations in Chennai city, India. Re- sults indicated that the PM2.5 concentration was highest in busy traffic site (mean = 22.7 ± 8.45 μg/m$^3$) and lowest in urban background (mean = 9.3 ± 5.75 μg/m$^3$). Whereas, the CO concentration was lowest at beach road (mean = 0.26 ± 0.01 ppm). Not much variation was observed in the average concentrations of NO$_2$ and O$_3$. On the other hand, while travelling in buses, higher concentration of CO and NO2 were observed during the morning and evening periods due to the peaking traffic flow. On contrary O$_3$ concentration was found to be highest during afternoon due to photochemical reactions.

Seema Khadirnaikar

Research Scholar

My research interests include application of supervised and unupervised machine learning techniques to precision medicine.