SARDO: An Automated Search-and-Rescue Drone-Based Solution for Victims Localization

被引:65
作者
Albanese, Antonio [1 ,3 ]
Sciancalepore, Vincenzo [1 ]
Costa-Perez, Xavier [2 ,4 ,5 ]
机构
[1] NEC Labs Europe, D-69115 Heidelberg, Germany
[2] NEC Labs Europe, 5G Networks R&D, D-69115 Heidelberg, Germany
[3] Univ Carlos III Madrid, Leganes 28911, Spain
[4] i2CAT Fdn, Barcelona 08034, Spain
[5] ICREA, Barcelona 08034, Spain
基金
欧盟地平线“2020”;
关键词
UAV-based cellular coverage; search and rescue operations; single-UAV localization; pseudo-trilateration; convolutional neural network (CNN); long short-term memory (LSTM); NEURAL-NETWORKS; ALGORITHMS; 5G;
D O I
10.1109/TMC.2021.3051273
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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-toreach areas and cellular networks are down. In this paper we present SARDO, a drone-based search and rescue solution that leverages 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 [1], show that SARDO rapidly determines the location of mobile phones (similar to 3 min/UE) in a given area with an accuracy of few tens of meters and at a low battery consumption cost (similar to 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.
引用
收藏
页码:3312 / 3325
页数:14
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