Multi-city hyperlocal environmental monitoring using distributed low-cost sensor network

The proposed data project is aimed at mapping ambient environmental conditions, which is highly resolved both spatially and temporally, across multiple cities in India. Current techniques for ambient air quality monitoring involve installation of environmental monitoring stations at fixed locations across the city. These stations are sparsely distributed owing to high costs associated with deployment and maintenance. As a result, the information from these stations can only be used as an indicator for the entire city as a whole. Ambient air quality can vary drastically across locations that are barely a few hundred meters apart. The proposed project would involve building a network of low cost, vehicle mounted environmental monitoring devices which would crisscross the city. Each device has 7 sensors that are capable of measuring up to 25 environmental parameters ranging from air quality information to solar intensity and even road condition. Modular hardware design allows for easy swapping and upgradation of the sensors. These distributed units would be capable of collecting environmental data with unprecedented spatial resolution. These IoT units are location aware and have bidirectional communication with a central server, sending data samples once every 20 seconds. This would enable near real-time, location specific tracking of environmental conditions. This high-resolution data combined with analytical tools would offer deeper insights on location specific environmental conditions prevailing within a city. Data from the low-cost sensors, in their raw form, are not comparable to that obtained from the gold standard device. Methods to calibrate and standardize sensors in order to improve fidelity of the data will be explored through this project. At the end of this project, we will develop pan-India environmental data that can be an incredible resource for researchers working in the area of data science to answer many questions of practical social significance.