Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 Annals of Computer Science and Information Systems

1 2022

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: early detection of forest fires

Sortuj według:

Ogranicz wyniki do:

Development of a Smart System for Early Detection of Forest Fires based on Unmanned Aerial Vehicles

Hristov Georgi, Le Chi Hieu, Yotov Yavor, Nguyen Ho Quang, Ab Patar Mohd Nor Azmi, Zlatov Nikolay, Kinaneva Diyana, Gao James, Huynh Le Minh, Mahmud Jamaluddin, Zahariev Plamen, Georgiev Georgi, Chu Anh My, Bui Trung Thanh, Packianather Michael S.

Annals of Computer Science and Information Systems

2022

Vol. 33

135--140

The naturally occurring wildfires and the peoplerelated 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 fullscale 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 fixedwing 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 realtime 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 THEASISM system are presented and briefly discussed.