论文标题
Sardo:一种自动搜索和基于受害者本地化的基于搜索无人机的解决方案
SARDO: An Automated Search-and-Rescue Drone-based Solution for Victims Localization
论文作者
论文摘要
每年自然灾害会影响数百万人。在最短的时间里寻找失踪人员对于减少死亡人数至关重要。当受害者分布在大型和/或难以到达的区域,并且蜂窝网络下降时,这项任务尤其具有挑战性。在本文中,我们介绍了Sardo,这是一种基于无人机的搜索解决方案,该解决方案利用了社会中手机的高渗透率来定位失踪人员。 Sardo是一种自主,基于无人机的移动网络解决方案,不需要基础架构支持或移动电话修改。它建立在新颖的概念上,例如伪经训练,并结合机器学习技术,可有效地在给定区域定位手机。我们的结果在现场审判中实现了原型,表明Sardo迅速确定手机(〜3分钟/UE)在给定区域的位置,其准确性为几十米,电池消耗量低(约5%)。灾难情景的最新本地化解决方案依赖于移动基础架构支持,要么利用在人/计算机视觉,IR,基于热的本地化的板载摄像头。据我们所知,Sardo是第一个基于无人机的蜂窝搜索解决方案,能够通过手机准确地定位缺失的受害者。
Natural disasters affect millions of people every year. Finding missing persons in the shortest possible time is of crucial importance to reduce the death toll. This task is especially challenging when victims are sparsely distributed in large and/or difficult-to-reach areas and cellular networks are down. In this paper we present SARDO, a drone-based search and rescue solution that exploits the high penetration rate of mobile phones in the society to localize missing people. SARDO is an autonomous, all-in-one drone-based mobile network solution that does not require infrastructure support or mobile phones modifications. It builds on novel concepts such as pseudo-trilateration combined with machine-learning techniques to efficiently locate mobile phones in a given area. Our results, with a prototype implementation in a field-trial, show that SARDO rapidly determines the location of mobile phones (~3 min/UE) in a given area with an accuracy of few tens of meters and at a low battery consumption cost (~5%). State-of-the-art localization solutions for disaster scenarios rely either on mobile infrastructure support or exploit onboard cameras for human/computer vision, IR, thermal-based localization. To the best of our knowledge, SARDO is the first drone-based cellular search-and-rescue solution able to accurately localize missing victims through mobile phones.