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Abstract <p>Remote monitoring of forested areas in hardly accessible places for early fire detection is examined. Automation methods and technologies are analyzed, including the use of unmanned aerial vehicles and neural network algorithms for detecting flames and smoke in images obtained from remote operational monitoring cameras. A solution is proposed for organizing wireless communication and data transmission to emergency response centers on the basis of a prototype energy-efficient ad-hoc network. This network can be used under the constraints imposed by terrain, remoteness, and territory size, and allows one to take into account weather conditions and various geographic features of the region where video surveillance is organized. Test results are presented for both the prototype of the entire fire detection information system and the throughput of the ad-hoc network created during this work. Conclusions are drawn regarding the development prospects of the proposed hardware and software system.</p>

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Organizing Data Transfer for Early Detection of Forest Fire Sources in Hardly Accessible Areas

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • E. V. Vaits,
  • P. A. Mikhalev,
  • D. P. Posevin,
  • A. S. Tolpygin

摘要

Abstract

Remote monitoring of forested areas in hardly accessible places for early fire detection is examined. Automation methods and technologies are analyzed, including the use of unmanned aerial vehicles and neural network algorithms for detecting flames and smoke in images obtained from remote operational monitoring cameras. A solution is proposed for organizing wireless communication and data transmission to emergency response centers on the basis of a prototype energy-efficient ad-hoc network. This network can be used under the constraints imposed by terrain, remoteness, and territory size, and allows one to take into account weather conditions and various geographic features of the region where video surveillance is organized. Test results are presented for both the prototype of the entire fire detection information system and the throughput of the ad-hoc network created during this work. Conclusions are drawn regarding the development prospects of the proposed hardware and software system.