  Air pollution is ranked as the second most serious risk for public health in
India after malnutrition. The lack of spatially and temporally distributed air
quality information prevents a scientific study on its impact on human health
and on the national economy. In this paper, we present our initial efforts
toward SATVAM, Streaming Analytics over Temporal Variables for Air quality
Monitoring, that aims to address this gap. We introduce the multi-disciplinary,
multi-institutional project and some of the key IoT technologies used. These
cut across hardware integration of gas sensors with a wireless mote packaging,
design of the wireless sensor network using 6LoWPAN and RPL, and integration
with a cloud backend for data acquisition and analysis. The outcome of our
initial deployment will inform an improved design that will enable affordable
and manageable monitoring at the city scale. This should lead to data-driven
policies for urban air quality management.
