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This article presents a novel approach for real-time flame detection using UAVs and MATLAB. The proposed system leverages the aerial capabilities of UAVs, allowing for a comprehensive view of the monitored area and reducing response times. Equipped with high-resolution cameras, the UAVs capture live video feeds, which are then processed using a custom-designed MATLAB program. Advanced image processing techniques can be implements with MATLAB software and Type-2 Fuzzy Logic can be used for robust and accurate flame detection. In this study, we discuss the development of the MATLAB-based flame detection algorithm, which combines spatial and temporal features to distinguish flames from other dynamic objects and environmental changes. Type-2 Fuzzy Logic is integrated into the algorithm to handle uncertainty and imprecision in flame detection, making the system more resilient to variations in environmental conditions. Overall, this research contributes to the field of fire safety and surveillance systems by presenting a cutting-edge approach to real-time flame detection. The combination of UAVs and MATLAB, as well as the use of, type-2 fuzzy logic systems can pave the way for more efficient and dependable fire detection systems, ultimately improving public safety and disaster management efforts. Because continuous surveillance cannot be done with old video surveillance systems. Integration with systems that automatically detect and recognize objects is used for continuous monitoring. The proposed system uses the aerial capabilities of unmanned aerial vehicles, provides a comprehensive overview of the controlled area and reduces response time. Drones equipped with high-speed cameras record video streams in real time and are processed by MATLAB software. Type-2 fuzzy logic systems can be used to accurately determine the location of the fire. In the article, parameters such as temperature change, the degree of illumination of the flame during a fire and distance were taken as the main variables and implemented in the MATLAB package for type-2 fuzzy logic systems.

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Fire Detection by Unmanned Aerial Vehicle Using Fuzzy Systems

  • 会议论文

  • 发表日期：

    2025年

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  • А. B. Sultanova,
  • T. A. Safarov

摘要

This article presents a novel approach for real-time flame detection using UAVs and MATLAB. The proposed system leverages the aerial capabilities of UAVs, allowing for a comprehensive view of the monitored area and reducing response times. Equipped with high-resolution cameras, the UAVs capture live video feeds, which are then processed using a custom-designed MATLAB program. Advanced image processing techniques can be implements with MATLAB software and Type-2 Fuzzy Logic can be used for robust and accurate flame detection. In this study, we discuss the development of the MATLAB-based flame detection algorithm, which combines spatial and temporal features to distinguish flames from other dynamic objects and environmental changes. Type-2 Fuzzy Logic is integrated into the algorithm to handle uncertainty and imprecision in flame detection, making the system more resilient to variations in environmental conditions. Overall, this research contributes to the field of fire safety and surveillance systems by presenting a cutting-edge approach to real-time flame detection. The combination of UAVs and MATLAB, as well as the use of, type-2 fuzzy logic systems can pave the way for more efficient and dependable fire detection systems, ultimately improving public safety and disaster management efforts. Because continuous surveillance cannot be done with old video surveillance systems. Integration with systems that automatically detect and recognize objects is used for continuous monitoring. The proposed system uses the aerial capabilities of unmanned aerial vehicles, provides a comprehensive overview of the controlled area and reduces response time. Drones equipped with high-speed cameras record video streams in real time and are processed by MATLAB software. Type-2 fuzzy logic systems can be used to accurately determine the location of the fire. In the article, parameters such as temperature change, the degree of illumination of the flame during a fire and distance were taken as the main variables and implemented in the MATLAB package for type-2 fuzzy logic systems.