A UAV aided lightweight target information collection and detection approach

Meng Huang, Hanming Li, Yina Zhou,Ting Ma,Jinshan Su,Haibo Zhou

Peer-to-Peer Networking and Applications(2024)

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摘要
With the resumption of the World Cup and various concerts, the number of heavily crowded scenarios grows intensely. In these cases, it poses new challenges to massive information collection and lightweight target detection. Fortunately, the booming development of unmanned aerial vehicle (UAV) technology provides a highly flexible and cost-effective solution in many scenarios. This paper proposes a UAV aided lightweight target information collection and detection approach, where the target information is carried to a terrestrial distributed platform by a UAV and then a fast target detection is implemented. Firstly, we implement a 3D trajectory optimization for the UAV by minimizing the information collection time. Secondly, we design a lightweight target detection algorithm based on UAV loadable ARM (Advanced RISC Machines) architecture edge computing device. Finally, a terrestrial distributed processing platform is established. To ensure the stability and reliability of the target detection system, each module is tested separately. Numerical simulations show that, with the target detection module deployed on the Jetson Xavier NX edge computing platform for testing, the proposed target detection approach can achieve a detection accuracy of 89.5 % and 71FPS detection speed using GPU acceleration compared with state-of-the-art methods.
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关键词
UAV,Trajectory optimization,Edge computing,Distributed computation
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