PdUC-D: A Discretized UAV Guidance System for Air Pollution Monitoring Tasks

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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.

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Alvear, O., Calafate, C. T., Zema, N. R., Natalizio, E., Hernández-Orallo, E., Cano, J. C., & Manzoni, P. (2018). PdUC-D: A Discretized UAV Guidance System for Air Pollution Monitoring Tasks. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 233, pp. 385–394). Springer Verlag. https://doi.org/10.1007/978-3-319-76111-4_38

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