Performance evaluation of monitoring IoT systems using LoRaWan

The proliferation of smart devices, or even better, IoT devices, has led to the widespread development of applications that take advantage of these devices. Of particular interest is the precise localization of such a device. However, these use cases become extremely difficult when connectivity to end-devices is required even in areas where the signal is too low or different technologies co-exist for the transmission of the data. In this research work, we study LoRaWan and Wi-Fi as two possible candidates for data transmission. We are particularly focused on the study of the above technologies in terms of performance as well as application development that can be used as rescue monitoring systems. For this reason, we start by describing LoRa as an ideal low power and long-distance communication protocol on the IoT devices compared to the Wi-Fi network. We perform various simulations in terms of time on air transmission, bit error rate by changing important metrics to study the behavior of the whole mechanism. Based on our simulations, the main findings highlight that the contribution of a spreading factor and bandwidth optimizations can be applied to real hardware for real search and rescue (SAR) cases giving improved results in case of coverage and battery extension applications. As a continuation of our research, we developed a monitor application that collects and visualizes data from end-nodes (wearables). These data are processed gateway and network server to The Things Network (TTN) for further analysis. The proposed solution can be used in different rescue monitor scenarios such as identifying and find individuals of vulnerable groups or those belonging to group of people with a high probability of being lost. The purpose of the above solution is to overcome monitor problems on SAR cases, compare with WiFi and suggest a module supporting both technologies in order to be used in real experiments.