Data Science and IoT for addressing ambient air sanctity
Ambient air quality is a dynamic parameter that shows a high degree of spatiotemporal variation. It is known to impact human life and health. Obtaining meaningful estimates of human exposure to air pollutants is key to mitigating its ill effects. Current air quality monitoring regime consists of expensive, static monitoring stations that are sparsely distributed across a city which in turn results in poor spatial resolution. This particular work, accomplished under project Kaatru, demonstrates the efficacy of low-cost sensor based, vehicle mounted, mobile monitoring paradigm in hyperlocal air quality assessment.
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