We are designing a robust and data-driven networked drone system that can efficiently navigate to perform the accurate air-pollution mapping. Conventionally, drone-based gas sensing solutions use traditional rotatory-wing flight systems equipped with large propellers, which allow them to hover at space points during the data collection process. That is, hovering is required in order to cope with the relatively high response time of air pollution sensors. Nevertheless, the large propellers of traditional drones generate an undesired strong airflow that has a negative impact on the quality of gas sensing as demonstrated in multiple prior works. In contrast, we design the first end-to-end gas-sensing balloon-based drone network system that leverages helium for a more efficient floatability. We experimentally evaluate the potential of balloon-based drones for gas sensing and aim to identify the benefits of the helium-powered flight mechanism on the accuracy of air pollution mapping compared to traditional rotatory-wing drones.
Publications
- Zhambyl Shaikhanov, Ahmed Boubrima, and Edward W. Knightly. “FALCON: a Networked Drone System for Sensing, Localizing, and Approaching RF targets.” IEEE Internet of Things Journal (IEEE IoT 2022)