Low Power Wide Area Network (LPWAN) technologies 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 40-60m in location positioning, ideal for search and rescue use cases.
We finally summarize the above algorithms’ estimation and general behavior in a SAR system.