PdUC-D: a discretized UAV guidance system for air pollution monitoring tasks

Abstract

Discretization is one of the most efficient mathematical approaches to simplify (optimize) a system by transforming a continuous domain into its discrete counterpart. In this paper, by adopting space discretization, we have modified the previously proposed solution called PdUC (Pollution-driven UAV Control), which is a protocol designed to guide UAVs that monitor air quality in a specific area by focusing on the most polluted areas. The improvement proposed in this paper, called PdUC-D, consists of an optimization whereby UAVs only move between the central tile positions of a discretized space, avoiding to monitor locations separated by small distances, and whose actual differences in terms of air quality are barely noticeable. Experimental results show that PdUC-D drastically reduces convergence time compared to the original PdUC proposal without loss of accuracy. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.