Mitigating Slow Dynamics of Low-Cost Chemical Sensors for Mobile Air Quality Monitoring Sensor Networks

摘要: The last decade has seen a growing interest in air quality monitoring using networks of wireless low-cost sensor platforms. One the unifying characteristics chemical sensors typically used real-world deployments is their slow response time. While impact dynamics can largely be neglected when considering static scenarios, mobile applications measurements should not considered as point (i.e. instantaneous space and time). In this paper, we study on measurement accuracy locality through systematic experiments controlled environment wind tunnel. We then propose two methods for dealing with problem: (i) reducing effect sensor's by an open active sampler, (ii) estimating underlying true signal model deconvolution technique. consider performance metrics evaluation: localization specific field features root mean squared error estimation. Finally, show that technique results consistent improvement all both metrics, while sniffer design provides advantage only feature localization, particularly highest movement speed.