Cooperative control of multiple UAVs for forest fire monitoring and detection

Author(s):  
Khaled A. Ghamry ◽  
Youmin Zhang
2015 ◽  
Vol 45 (7) ◽  
pp. 783-792 ◽  
Author(s):  
Chi Yuan ◽  
Youmin Zhang ◽  
Zhixiang Liu

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.


Author(s):  
Ying Wang ◽  
Yiding Liu ◽  
Minna Xia

Big data is featured by multiple sources and heterogeneity. Based on the big data platform of Hadoop and spark, a hybrid analysis on forest fire is built in this study. This platform combines the big data analysis and processing technology, and learns from the research results of different technical fields, such as forest fire monitoring. In this system, HDFS of Hadoop is used to store all kinds of data, spark module is used to provide various big data analysis methods, and visualization tools are used to realize the visualization of analysis results, such as Echarts, ArcGIS and unity3d. Finally, an experiment for forest fire point detection is designed so as to corroborate the feasibility and effectiveness, and provide some meaningful guidance for the follow-up research and the establishment of forest fire monitoring and visualized early warning big data platform. However, there are two shortcomings in this experiment: more data types should be selected. At the same time, if the original data can be converted to XML format, the compatibility is better. It is expected that the above problems can be solved in the follow-up research.


2021 ◽  
Vol 111 ◽  
pp. 106574
Author(s):  
Francesco De Vivo ◽  
Manuela Battipede ◽  
Eric Johnson

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