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Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering

Annals of Computer Science and Information Systems, Volume 33

Design of scheduling algorithms for UAVs to Detect Air Pollution Sources from Chimneys in Industrial Area

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DOI: http://dx.doi.org/10.15439/2022R20

Citation: Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering, Vu Dinh Khoa, Shivani Agarwal, Gloria Jeanette Rincon Aponte, Nguyen Thi Hong Nga, Vijender Kumar Solanki, Ewa Ziemba (eds). ACSIS, Vol. 33, pages 273–278 ()

Full text

Abstract. With the rapid development of Unmanned Aerial Vehicle (UAV), many related applications using UAVs is to monitor air quality in urban, rural or industrial areas. They often focus on how to monitor the propagation of air pollution, provided the pollution sources should be positioned with permanently placed wireless sensors. However, it is hard and time-consuming to identify pollution sources due to a number of chimneys in industrial areas. Therefore, to air pollution source detection in the minimum search time from the chimneys with fixed locations in an industrial park using one or more UAVs. In this paper, we propose two heuristics algorithms for air-pollution-source detection by UAVs including Interference-Graph- Based Algorithm (IGBA), and Extended Interference-Graph-Based Algorithm (EIGBA). As a result, the detection time by these proposed algorithms compared with that by the Traveling Salesman Problem (TSP) algorithm air pollution source detection time is significantly reduced.

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