  Current air pollution monitoring systems are bulky and expensive resulting in
a very sparse deployment. In addition, the data from these monitoring stations
may not be easily accessible. This paper focuses on studying the dense
deployment based air pollution monitoring using IoT enabled low-cost sensor
nodes. For this, total nine low-cost IoT nodes monitoring particulate matter
(PM), which is one of the most dominant pollutants, are deployed in a small
educational campus in Indian city of Hyderabad. Out of these, eight IoT nodes
were developed at IIIT-H while one was bought off the shelf. A web based
dashboard website is developed to easily monitor the real-time PM values. The
data is collected from these nodes for more than five months. Different
analyses such as correlation and spatial interpolation are done on the data to
understand efficacy of dense deployment in better understanding the spatial
variability and time-dependent changes to the local pollution indicators.
