基于无人机的火灾探测系统

Cong Xiong, Anning Yu, L. Rong, Jiaming Huang, Bocheng Wang, Hai-nan Liu
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引用次数: 4

摘要

无人机由于成本低、机动性强、鸟瞰图宽等优点,在巡检和应急救援领域得到越来越广泛的应用。传统的火灾探测方法大多基于RGB颜色模型,其探测速度和精度都存在不足。本文提出了一种基于自主无人机平台的火灾探测方法。无人机按照指定路线飞行,搭载搭载YOLOv3火灾探测算法的Ultra96-V2开发板,作为边缘计算设备,将探测结果实时传回地面站。实验结果表明,该算法的识别率为80%,模型内存压缩率大于75%,实时检测帧率大于3 FPS。
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Fire detection system based on unmanned aerial vehicle
Because of the low cost, strong mobility, and wide aerial view, the UAV is more and more widely used in the field of inspection and emergency rescue. Most of the traditional fire detection methods are based on the RGB color model, and their detection speed and accuracy are inadequate. In this paper, a fire detection method based on an autonomous drone platform is proposed. The drone flies on a designated route and carries an Ultra96-V2 development board with YOLOv3 fire detection algorithms deployed, which acts as an edge computing device to transmit the detection results back to the ground station in real time. Experimental results show that the recognition rate of the algorithm is 80%, the model memory compression is more than 75%, and the real-time detection frame rate is more than 3 FPS.
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