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Individual Status Recognition System Assisted by UAV in Post-Disaster

机译:无人机辅助灾后个人身份识别系统

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When natural disasters occur, there is a possibility of having many injured people in the disaster area. In the meanwhile, rescue teams have to aid these injured individuals as fast as possible. In this study, we proposed a recognition system of individual status to help rescue teams. Employing Unmanned Aerial Vehicles (UAVs) system after disaster occurrence gives many advantages. For instance, a UAV can cover a wide area and provide aerial photographs in a short period. This study aims to classify whether an individual status is standing, sitting, or lying on the ground by using supervised machine learning. Experiments revealed that the system is able to recognize all three types of individual status with an accuracy of 95.6%. Moreover, the authors confirmed the usefulness of using a UAV to recognize individuals in the post-disaster scenario.
机译:当自然灾害发生时,有可能在灾区有很多受伤的人。同时,救援队必须尽快援助这些受伤的人。在这项研究中,我们提出了一种个人身份识别系统来帮助救援队。灾难发生后使用无人飞行器(UAV)系统具有许多优势。例如,无人机可以覆盖广阔的区域并在短时间内提供航拍照片。这项研究旨在通过监督式机器学习对个人状态是站立,坐着还是躺在地上进行分类。实验表明,该系统能够识别所有三种类型的个人状态,准确率达95.6%。此外,作者们证实了在灾难后场景中使用无人机识别个人的有用性。

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