scholarly journals Improvement of forest fire monitoring system by expanding information and technological possibilities of modern quadcopters

2021 ◽  
pp. 33-46
Author(s):  
Olena Husak ◽  
Volodymyr Husak
Keyword(s):  
Information Technology ◽  
Early Detection ◽  
Unmanned Aerial Vehicles ◽  
Monitoring System ◽  
Forest Fire ◽  
Fire Protection ◽  
Forest Fires ◽  
High Tech ◽  
Fire Monitoring ◽  
Aerial Vehicles

The article proposes a solution to an important problem — the development of an information technology based on expanding the functionality of non-specialized unmanned aerial vehicles (drones) for early detection of forest fires. The proposed information technology is designed to increase the effectiveness of monitoring forest fires. Тhe existing level of information technology does not fully settle the issue of reliable fire protection of forests. Today, there is a contradiction between the high cost of developing high-tech fire-fighting equipment and lack of its efficiency. The elimination of this contradiction will be facilitated by the involvement of additional non-technical and technical resources in the information technology of early detection of forest fire hotspots. The results of the analysis of the use of modern drones prove that the involvement of unmanned aerial vehicles significantly increases the efficiency of many types of monitoring and they can successfully be used to solve the problems of early detection of forest fire hotspots. The results of experiments are presented, which were carried out both for a series of digital images and for video.

A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques

2015 ◽  
Vol 45 (7) ◽  
pp. 783-792 ◽  
Author(s):  
Chi Yuan ◽  
Youmin Zhang ◽  
Zhixiang Liu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Forest Fire ◽  
Forest Fires ◽  
Cooperative Control ◽  
Fire Detection ◽  
Fire Monitoring ◽  
Diagnosis And Prognosis ◽  
Aerial Vehicles ◽  
Remote Sensing Techniques ◽  
Operational Range

Because of their rapid maneuverability, extended operational range, and improved personnel safety, unmanned aerial vehicles (UAVs) with vision-based systems have great potential for monitoring, detecting, and fighting forest fires. Over the last decade, UAV-based forest fire fighting technology has shown increasing promise. This paper presents a systematic overview of current progress in this field. First, a brief review of the development and system architecture of UAV systems for forest fire monitoring, detection, and fighting is provided. Next, technologies related to UAV forest fire monitoring, detection, and fighting are briefly reviewed, including those associated with fire detection, diagnosis, and prognosis, image vibration elimination, and cooperative control of UAVs. The final section outlines existing challenges and potential solutions in the application of UAVs to forest firefighting.

scholarly journals The Problem of Timely Detection and Elimination of Forest Fires

2021 ◽  
Vol 7 (6) ◽  
Author(s):  
N. Veretennikova ◽  
V. Kislov ◽  
K. Eremenko
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Detection ◽  
Aerial Vehicles

Up to 35 thousand forest fires are registered in Russia annually, the area of fire of which is up to 2.5 million hectares. The use of unmanned aerial vehicles as one of the effective ways to detect and prevent forest fires. The use of UAVs has more advantages over other means of fire detection. In conclusion, the authors conclude that if only an incipient forest fire can be detected, it will prevent large economic and environmental losses.

scholarly journals Forest Farm Fire Drone Monitoring System Based on Deep Learning and Unmanned Aerial Vehicle Imagery

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Shaoxiong Zheng ◽  
Weixing Wang ◽  
Zeqian Liu ◽  
Zepeng Wu
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Monitoring System ◽  
Forest Fire ◽  
Forest Fires ◽  
Operating Cost ◽  
Operating Efficiency ◽  
Rescue Operation ◽  
Fire Monitoring ◽  
Forest Farm

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.

Network-centric approach to prevention and elimination of forest fires based on integration information resources and systems

2020 ◽  
Vol 89 ◽  
pp. 98-109
Author(s):  
S. A. Barkovsky ◽  
◽  
A. V. Spiridonov ◽  
A. I. Ovsyanik ◽  
V. L. Semikov ◽  
...  
Keyword(s):  
Monitoring System ◽  
Forest Fire ◽  
Forest Fires ◽  
Information Resources ◽  
Fire Monitoring ◽  
Digital Maps ◽  
Emergency Situations ◽  
Operational Information ◽  
Current Situation Analysis ◽  
Forest Fire Prevention

Introduction. The article analyzes the use of modern information resources and systems in extinguishing wildfires. The approach uses a network-centric system for modern resources and systems integration. Goals and objectives. The purpose of the study is to identify and improve methods and tools for assessing forest fire prevention based on the integration of information resources and systems. Methods. Information-based methods and systems that allow simultaneous analysis of multi-dimensional data using digital maps, simplify the prediction and assessment of the complex effects of forest fires are considered, make it possible to quickly identify the anomalies and take the necessary measures to eliminate them. Results and discussion. Based on the results of the analysis, a generalized structure of the forest fire monitoring system was developed using a network-centric approach. Conclusion. A network-centric monitoring system combines all information resources and systems at all levels and directions. Early monitoring of the current situation, analysis of current operational information about identified thermal points, and modeling of possible scenarios for the development of the situation allows the most effective approach to solving problems of protecting the population and territory from the consequences of forest fires. Combining the advantages of individual modern technologies into a single distributed network-centric system makes it possible to effectively implement the elimination of the consequences of all types of emergencies. Key words: network-centric system, forest fires, forecasting and prevention of emergency situations, information resources and systems.

Computer Vision Method for Forest Fires Detection Based on RGB Images Obtained by Unmanned Motor Glider

2021 ◽  
pp. 71-78
Author(s):  
Michael Yu. Kataev ◽  
Eugene Yu. Kartashov
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Detection ◽  
Monitoring Systems ◽  
Colour Space ◽  
Fire Monitoring ◽  
Aerial Vehicle ◽  
Rgb Images ◽  
Forest Fire Detection

The article proposes a method (algorithm) of forest fire detection by means of RGB images obtained by using an unmanned aerial vehicle (motor glider). It includes several stages associated with background detection and subtraction and recognition of fire areas by means of RGB colour space. The proposed method was tested using images of forest fires. It is proposed to use unmanned aerial vehicles capable to monitor large areas continuously for several hours. The results of calculations are shown, which demonstrate that the proposed method allows us to detect areas of images occupied by forest fires and may be used in automatic forest fire monitoring systems.

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