Using UAV-Based Systems to Monitor Air Pollution in Areas with Poor Accessibility

[EN] Air pollution monitoring has recently become an issue of utmost importance in our society. Despite the fact that crowdsensing approaches could be an adequate solution for urban areas, they cannot be implemented in rural environments. Instead, deploying a fleet of UAVs could be considered an acceptable alternative. Embracing this approach, this paper proposes the use of UAVs equipped with off-the-shelf sensors to perform air pollution monitoring tasks. These UAVs are guided by our proposed Pollution-driven UAV Control (PdUC) algorithm, which is based on a chemotaxis metaheuristic and a local particle swarm optimization strategy. Together, they allow automatically performing the monitoring of a specified area using UAVs. Experimental results show that, when using PdUC, an implicit priority guides the construction of pollution maps by focusing on areas where the pollutants' concentration is higher. This way, accurate maps can be constructed in a faster manner when compared to other strategies. The PdUC scheme is compared against various standard mobility models through simulation, showing that it achieves better performance. In particular, it is able to find the most polluted areas with more accuracy and provides a higher coverage within the time bounds defined by the UAV flight time.
This work has been partially carried out in the framework of the DIVINA Challenge Team, which is funded under the Labex MS2T program. Labex MS2T is supported by the French Government, through the program "Investments for the Future" managed by the National Agency for Research (Reference: ANR-11-IDEX-0004-02). This work was also supported by the "Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a Retos de la Sociedad, Proyecto I+D+I TEC2014-52690-R," the "Programa de Becas SENESCYT de la Republica del Ecuador," and the Research Direction of University of Cuenca.