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

Vinh Le Van, Huyen Ngo Thanh

Annals of Computer Science and Information Systems

2022

Vol. 33

273--278

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.