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Optimizing the spatial location of medical drones

机译:优化医疗无人机的空间位置

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Unmanned aerial vehicles (UAVs) or drones are increasingly proposed for medical uses due to their potential to transport medical supplies quickly and efficiently. A prototype medical drone that is equipped with an on-board automated external defibrillator (AED) was announced recently to significantly reduce the time it takes for an AED to arrive to a patient's side. As drones are battery-operated and have limited service range, a network of medical drones is required to adequately provide service to a large area. This paper developed a new spatial optimization model, the backup coverage location problem with complementary coverage (BCLP-CC), to aid in the deployment of a network of AED enabled medical drones. By explicitly integrating backup coverage and continuously distributed demand, the BCLP-CC can optimally place drones and the corresponding launch sites while significantly improving backup coverage with minimal loss of primary coverage. Our results show that 90.4% of historical out-of-hospital cardiac arrests in Salt Lake County can be responded to within 1 min by using 71 drones and 68 launch sites. In addition, 58.9% of incidents can be served by two or more drones, a significant improvement over existing models. This study shows that drones could significantly reduce life-saving equipment travel times for victims of cardiac arrest by appropriately siting them, which will motivate further research in using UAVs or drones for emergency medical purpose.
机译:由于其潜力能够快速有效地运输医疗用品,越来越多地提出了无人驾驶飞行器(无人机)或无人机。最近宣布配备有车载自动除尘器(AED)的原型医疗无人机,以显着减少AED到达患者侧面所需的时间。由于无人机是电池供电的并且服务范围有限,因此需要一种医疗无人机网络来充分为大面积提供服务。本文开发了一种新的空间优化模型,备份覆盖位置问题与互补覆盖率(BCLP-CC),有助于部署启用AED的医疗无人机网络。通过明确地集成备份覆盖范围和不断分布的需求,BCLP-CC可以最佳地放置无人机和相应的发射站点,同时显着提高备份覆盖,以最小的主要覆盖损失。我们的研究结果表明,盐湖县历史悠久的医院外逮捕的90.4%可以通过使用71个无人机和68个发射地点在1分钟内作出反应。此外,58.9%的事件可以由两种或更多种无人机服务,对现有模型的重大改进。本研究表明,通过适当地选中它们,无人机可以显着降低心脏捕获受害者的救生设备旅行时间,这将激励使用无人机或无人机进行紧急医疗目的的进一步研究。

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