Hristov, Georgi, Zlatov, Nikolay, Zahariev, Plamen, Le, Chi Hieu ORCID: 0000-0002-5168-2297, Kinaneva, Diyana, Georgiev, Georgi, Yotov, Yavor, Gao, Xiaoyu ORCID: 0000-0001-5625-3654, Chu, Anh My, Nguyen, Ho Quang, Huynh, Le Minh, Bui, Trung Thanh, Patar, Mohd Nor Azmi Ab, Mahmud, Jamaluddin and Packianather, Michael (2023) Development of a smart system for early detection of forest fires based on unmanned aerial vehicles. In: Annals of Computer Science and Information Systems - Proceedings of the Seventh International Conference on Research in Intelligent and Computing in Engineering (RICE 2022). November 11–12, 2022. Hung Yen University of Technology and Education, Vietnam. Polskie Towarzystwo Informatyczne, Warsaw, Poland, pp. 135-139. ISBN 978-8396589767; 978-8396589774 ISSN 2300-5963 (doi:https://doi.org/10.15439/978-83-965897-6-7)

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Abstract

The naturally occurring wildfires and the people-related forest fires are events, which in many cases have significant impact on the environment, the wildlife and the human population. The most devastating among these events usually start in unpopulated remote areas, which are difficult to inspect or are not constantly being monitored or observed. This gives the local small-sized fires enough time to evolve into full-scale wide-area disasters, which in turn makes their suppression and extinguishing very difficult. In this paper, we present an autonomous system for early detection of forest fires, named THEASIS-M. The presented system represents a solution that is based on a combination of innovative technologies, including computer vision algorithms, artificial intelligence and unmanned aerial vehicles. In the first part of the study, we provide an overview on the present applications of the UAVs in the forestry domain. The paper then introduces the general architecture of the THEASIS-M system and its components. The system itself is fully autonomous and is based on several different types of UAVs, including a fixed-wing drone, which provides the overall forest monitoring capabilities of the proposed solution, and a rotary-wing UAV that is used for confirmation and monitoring of the detected fire event. The widely used technologies for computer vision and image processing, which are used for the detection of fire and smoke in the real-time video streams sent from the UAVs to the ground control station, are highlighted in the next section of this study. Finally, the experimental tests and demonstrations of the proposed THEASIS-M system are presented and briefly discussed.

Item Type:	Conference Proceedings
Title of Proceedings:	Annals of Computer Science and Information Systems - Proceedings of the Seventh International Conference on Research in Intelligent and Computing in Engineering (RICE 2022). November 11–12, 2022. Hung Yen University of Technology and Education, Vietnam
Uncontrolled Keywords:	unmanned aerial vehicles; computer vision; Artificial Intelligence; early detection of forest fires; autonomous system for fire detections
Subjects:	Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Engineering (ENG)
Related URLs:	Publisher
Last Modified:	29 Mar 2023 08:01
URI:	http://gala.gre.ac.uk/id/eprint/38823

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