To improve air quality by providing real-time solutions for monitoring and managemen to support policy makers, regulatory authorities, climate researchers, and facility managers to take data-based decisions through low-cost sensor networks and climate sciences analytics platforms.
An array of air quality monitoring solutions, including products that can measure ambient air quality, indoor air quality, oxygen concentration and state of the art analytics dashboard.
The SATVAM (Streaming Analytics over Temporal Variables from Air quality Monitoring) initiative has been developing low-cost air quality (LCAQ) sensor networks based on highly portable IoT software platforms. These LCAQ devices include PM2.5 as well as gas sensors. A unique feature of this low-cost sensor deployment was a swap-out experiment wherein four of the six sensors were relocated to different sites in the two phases. The swap-out experiment was crucial in investigating the efficacy of calibration models when applied to weather and air quality conditions vastly different from those present during calibration. A novel local calibration algorithm was developed based on metric learning that offers stable and accurate calibration performance.
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