Geolocation analysis for Search And Rescue systems using LoRaWAN,International Journal of Communication Systems

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Geolocation analysis for Search And Rescue systems using LoRaWAN
International Journal of Communication Systems ( IF 1.7 ) Pub Date : 2020-08-17 , DOI: 10.1002/dac.4593
Christos Bouras ₁ , Apostolos Gkamas ₂ , Vasileios Kokkinos ₁ , Nikolaos Papachristos ₁

Affiliation

Low‐power wide‐area network (LPWAN) technologies are aiming to provide power‐efficient solutions to the field of Internet of Things (IoT). Over the last years, we have seen a significant development within the area of IoT applications. For many applications, the problem of localization (i.e., determine the physical location of nodes) is critical. An area study of such use case is also the rescue monitor systems. In this study, we start by describing a solution designed for the long range wide area network (LoRaWAN) to localize position of IoT modules such as wearables used from vulnerable groups. Through performance study of the behavior of a LoRaWAN channel and using trilateration and RSSI information, the localization of an IoT wearable can be acquired within a small range. Routing people in need is one of the use cases the above mechanism could be integrated so as to be able to be tracked by familiar people. After that, we evaluate the usage of mathematical model of multilateration algorithms using time difference of arrival (TDoA) as a solution for positioning over LoRaWAN. The research is carried out using simulations in Python by configuring the constant positions of the Gateways inside an outdoor area. The proposed algorithms can be integrated in application for tracking people at any time and especially routing people from vulnerable groups. Through multilateration and algorithm's prediction, we can have an accuracy of 40–60 m in location positioning, ideal for search and rescue use cases. We finally summarize the above algorithms' estimation and general behavior in a SAR system.

中文翻译：

使用LoRaWAN的搜索和救援系统的地理位置分析

低功耗广域网（LPWAN）技术旨在为物联网（IoT）领域提供节能解决方案。在过去的几年中，我们看到了物联网应用领域的重大发展。对于许多应用程序，本地化问题（即确定节点的物理位置）至关重要。这种用例的领域研究也是救援监视系统。在本研究中，我们首先描述一种为远程广域网（LoRaWAN）设计的解决方案，以定位IoT模块的位置，例如易受伤害群体使用的可穿戴设备。通过对LoRaWAN通道行为的性能研究并使用三边测量和RSSI信息，可以在很小的范围内获得IoT可穿戴设备的本地化。路由有需要的人是上述机制之一，可以集成在一起，以便熟悉的人可以跟踪。之后，我们评估使用到达时间差（TDoA）作为LoRaWAN定位解决方案的多纬度算法数学模型的使用。通过在室外区域配置网关的恒定位置，使用Python中的模拟进行了研究。可以将所提出的算法集成到应用程序中，以随时跟踪人员，尤其是将人员从易受攻击的人群中路由出去。通过多边定位和算法的预测，我们可以实现40-60 m的定位精度，非常适合搜索和救援用例。最后，我们总结了上述算法在SAR系统中的估计和一般行为。

更新日期：2020-10-16

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