Framework and Method for Measurement of Particulate Matter Concentration using Low Cost Sensors

Rapid urbanisation and infrastructure shortcomings leading to heavy traffic, heavy construction activities are major contributors to emission of particulate matter into the ambient atmosphere. This is especially true in developing countries, such as India and China. There have been numerous attempts from government authorities and civic agencies to curtail pollution, but these efforts have been in vain. Cities like Beijing, New Delhi suffer from extremely unhealthy air quality during multiple months of the year. Hence, the onus of keeping oneself safe from extreme affects of air pollution falls on the individual. The following study presents a method and framework to measure particulate matter (PM2.5) concentration using low cost sensors, and infer patterns from the data collected. The study uses a SDS011 high precision laser PM2.5 detector module combined with a raspberry pi, which communicates the measurements through message queueing telemetry transport (MQTT) protocol to a ponte server which inturn persists the data into a MongoDB, which can be consumed by algorithms for further analysis. For example, the data obtained from the sensors can be fused with data from measurement stations and geographical land use information to estimate dense spatio-temporal pollution maps which is the basis for computing individual exposure to pollutants.