基于无人机的5G和人工智能在大规模伤亡事件中的智能分诊系统。
Unmanned aerial vehicle based intelligent triage system in mass-casualty incidents using 5G and artificial intelligence.
作者信息
Lu Jiafa, Wang Xin, Chen Linghao, Sun Xuedong, Li Rui, Zhong Wanjing, Fu Yajing, Yang Le, Liu Weixiang, Han Wei
机构信息
Emergency Department of Shenzhen University General Hospital, Shenzhen 518055, China.
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
出版信息
World J Emerg Med. 2023;14(4):273-279. doi: 10.5847/wjem.j.1920-8642.2023.066.
BACKGROUND
Rapid on-site triage is critical after mass-casualty incidents (MCIs) and other mass injury events. Unmanned aerial vehicles (UAVs) have been used in MCIs to search and rescue wounded individuals, but they mainly depend on the UAV operator's experience. We used UAVs and artificial intelligence (AI) to provide a new technique for the triage of MCIs and more efficient solutions for emergency rescue.
METHODS
This was a preliminary experimental study. We developed an intelligent triage system based on two AI algorithms, namely OpenPose and YOLO. Volunteers were recruited to simulate the MCI scene and triage, combined with UAV and Fifth Generation (5G) Mobile Communication Technology real-time transmission technique, to achieve triage in the simulated MCI scene.
RESULTS
Seven postures were designed and recognized to achieve brief but meaningful triage in MCIs. Eight volunteers participated in the MCI simulation scenario. The results of simulation scenarios showed that the proposed method was feasible in tasks of triage for MCIs.
CONCLUSION
The proposed technique may provide an alternative technique for the triage of MCIs and is an innovative method in emergency rescue.
背景
在大规模伤亡事件（MCI）和其他大规模伤害事件发生后，快速现场分诊至关重要。无人驾驶飞行器（UAV）已被用于MCI中搜索和救援受伤人员，但它们主要依赖于无人机操作员的经验。我们使用无人机和人工智能（AI）为MCI的分诊提供一种新技术，并为紧急救援提供更有效的解决方案。
方法
这是一项初步实验研究。我们基于两种AI算法，即OpenPose和YOLO，开发了一种智能分诊系统。招募志愿者模拟MCI场景并进行分诊，结合无人机和第五代（5G）移动通信技术实时传输技术，以在模拟的MCI场景中实现分诊。
结果
设计并识别了七种姿势，以在MCI中实现简短但有意义的分诊。八名志愿者参与了MCI模拟场景。模拟场景结果表明，所提出的方法在MCI分诊任务中是可行的。
结论
所提出的技术可能为MCI的分诊提供一种替代技术，并且是紧急救援中的一种创新方法。
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