Development of Forest Fire Monitoring System Using a Long-Term Endurance Solar Powered Drone and Deep Learning

Author(s):  
Dong Ki Chung ◽  
Myung Hwa Lee ◽  
Hwi Young Kim ◽  
Jeong Yong Park ◽  
Im Pyeong Lee
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Shaoxiong Zheng ◽  
Weixing Wang ◽  
Zeqian Liu ◽  
Zepeng Wu

Forest fires represent one of the main problems threatening forest sustainability. Therefore, an early prevention system of forest fire is urgently needed. To address the problem of forest farm fire monitoring, this paper proposes a forest fire monitoring system based on drones and deep learning. The proposed system aims to solve the shortcomings of traditional forest fire monitoring systems, such as blind spots, poor real-time performance, expensive operational costs, and large resource consumption. The image processing techniques are used to determine whether the frame returned by a drone contains fire. This process is accomplished in real time, and the resultant information is used to decide whether a rescue operation is needed. The proposed method has simple operations, high operating efficiency, and low operating cost. The experimental results indicate that the relative accuracy of the proposed algorithm is 81.97%. In addition, the proposed technique provides a digital ability to monitor forest fires in real time effectively. Thus, it can assist in avoiding fire-related disasters and can significantly reduce the labor and other costs of forest fire disaster prevention and suppression.


2013 ◽  
Vol 760-762 ◽  
pp. 1043-1047
Author(s):  
Chun Lei Zhao ◽  
Xia Hou

In order to monitor the forest fire effectively and to reduce the loss caused by forest fire in North China areas, a forest fire monitoring system was designed. Based on satellite remote sensing data, GIS data and meteorological information, the system has functions such as processing of data, adjusting of forest fire index for judging hot spots, intelligent judging of hot spots, and analyzing of geographical information and weather condition of hot spots. Also fire information is issued on web and by short message service. The system makes the remote sensing monitoring of forest fire automatically.


2013 ◽  
Vol 26 (3) ◽  
pp. 303-316 ◽  
Author(s):  
Ljiljana Šerić ◽  
Maja Štula ◽  
Darko Stipaničev

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