Opportunistic Mobile Urban Sensing Technologies

With the rise of the internet of things and affordable sensing technologies, urban environmental data are becoming increasingly easier to collect. These emerging technologies are challenging the traditional stationary weather and air quality sensing stations, enabling the acquisition of urban environmental data affordably. In this context, pervasive urban sensing experiments are emerging. This research presents a low-cost mobile urban sensing technology to enable the acquisition of urban air quality data at high spatiotemporal resolutions. While in the last years there has been a rise in mobile urban sensing experimental campaigns, low cost and autonomous mobile sensing stations have not yet been effectively implemented for high spatial resolution urban environmental sensing. There are still many challenges to be addressed to aim for reliable and affordable mobile urban sensing protocols.

This research presents an autonomous and cost effective mobile urban sensing technology (MUST) for the acquisition of urban air quality data. Readily available air quality sensors for PM₁₀, PM_2.5, CO, O₃, NO₂, CO₂, temperature and humidity have been used and calibrated against laboratory and governmental reference sensors. The sensing kits are also equipped with a GPS shield that enables the kits to be geo-localized in real time. Furthermore, the kit also comprises a cellular antenna that enables the acquired data to be transmitted in near real time to an online database, and to remotely reboot or update the code loaded in the microcontroller. Through what we call opportunistic sensing, the sensing kit has been mounted on private vehicles, mail transportation vans and public buses to enable the acquisition of high spatial resolution urban air quality data without requiring the use of dedicated vehicles, or the preparation of specialized experimental campaigns. Finally, the MUST sensing kit hardware has been designed aiming to protect the interior electronics from water while enabling a sufficient air exchange rate for the effective functioning of the sensors. In order to quantify the ventilation potential of the sensor chamber contained within the sensing kit, fog visualization wind tunnel experiments have been performed.

MUST sensing kits were deployed over private vehicles and university logistic vans for a duration of 5 weeks between June and July 2019. As expected, the results of the data collected within Princeton University Campus showed that there are strong air quality gradients, especially between the inner campus and peripheral more urbanized areas, and between the Princeton township centre, and the areas in closer proximity to Route #1.