High resolution spatio-temporal monitoring of air pollutants using wireless sensor networks

Atmospheric pollutants, such as gases and particulate matters (PM) pose a threat to human health. In particular, there has been a strong focus on particulate matter as it is a common pollutant to cause population health hazards, especially respiratory illness. Monitoring of this pollutant is currently attained at low spatial resolutions due to the cost of accurate sensing devices. Even though these devices are highly accurate, given the distance they are placed apart from each other, the relevance of their measurements to an unmeasured spatial location in between sensors will be very low, which causes large estimation errors. In this paper, we present a solution by creating easy-to-implement wireless sensor network hardware equipped with inexpensive PM sensors to supplement the existing high accurate PM devices to improve estimation accuracy at higher spatial and temporal resolutions. The measurements collected from the real deployments of these sensors are analyzed using spatio-temporal estimation technique to demonstrate the ability to provide accurate estimation at unmeasured locations.