  Particulate matter (PM) is considered the primary contributor to air
pollution and has severe implications for general health. PM concentration has
high spatial variability and thus needs to be monitored locally. Traditional PM
monitoring setups are bulky, expensive and cannot be scaled for dense
deployments. This paper argues for a densely deployed network of IoT-enabled PM
monitoring devices using low-cost sensors. In this work, 49 devices were
deployed in a region of the Indian metropolitan city of Hyderabad out-of this,
43 devices were developed as part of this work and 6 devices were taken off the
shelf. The low-cost sensors were calibrated for seasonal variations using a
precise reference sensor. A thorough analysis of data collected for seven
months has been presented to establish the need for dense deployment of PM
monitoring devices. Different analyses such as mean, variance, spatial
interpolation and correlation have been employed to generate interesting
insights about temporal and seasonal variations of PM. In addition,
event-driven spatio-temporal analysis is done for PM values to understand the
impact of the bursting of firecrackers on the evening of the Diwali festival. A
web-based dashboard is designed for real-time data visualization.
