Research Article
PdUC-D: A Discretized UAV Guidance System for Air Pollution Monitoring Tasks
@INPROCEEDINGS{10.1007/978-3-319-76111-4_38, author={Oscar Alvear and Carlos Calafate and Nicola Zema and Enrico Natalizio and Enrique Hern\^{a}ndez-Orallo and Juan-Carlos Cano and Pietro Manzoni}, title={PdUC-D: A Discretized UAV Guidance System for Air Pollution Monitoring Tasks}, proceedings={Smart Objects and Technologies for Social Good. Third International Conference, GOODTECHS 2017, Pisa, Italy, November 29-30, 2017, Proceedings}, proceedings_a={GOODTECHS}, year={2018}, month={3}, keywords={UAV control system Air pollution monitoring Discretized system}, doi={10.1007/978-3-319-76111-4_38} }- Oscar Alvear
Carlos Calafate
Nicola Zema
Enrico Natalizio
Enrique Hernández-Orallo
Juan-Carlos Cano
Pietro Manzoni
Year: 2018
PdUC-D: A Discretized UAV Guidance System for Air Pollution Monitoring Tasks
GOODTECHS
Springer
DOI: 10.1007/978-3-319-76111-4_38
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.
