Enhancing measurement quality through active sampling in mobile air quality monitoring sensor networks

In recent years, a growing number of research groups have targeted the development and deployment of networks using low-cost chemical sensors for monitoring air quality. Due to economical reasoning, most of these systems make use of some sort of mobility to increase spatial coverage. The effect of mobility on measurement quality has, however, been largely neglected. The long response time of the chemical sensors typically used for this type of application, in conjunction with platform mobility, leads to significant signal distortion. While this problem can be addressed through signal deconvolution techniques, their effectiveness is limited by the typical poor Signal-to-Noise Ratio (SNR) of the measured signal. In this paper, we study the possibility of enhancing the measurement quality of chemical sensors through the use of active sampling (or sniffing). We propose different sniffer designs, employing both fans and pumps as actuators. Using a rigorous experimental framework, inside a wind tunnel, we study the ability of active samplers to increase measurement SNR, and thus indirectly to improve sensor dynamic response. We obtain a significant and consistent improvement in SNR for one of our pump-based sniffer designs. Finally, we validate the robustness of this signal enhancement in real-world conditions through an outdoor car-based experiment.