Understanding LoRaWAN Transmissions in Harsh Environments: A Measurement-Based Campaign Through Unmanned Aerial/Surface Vehicles

Along with the ubiquity of various Internet of Things (IoT) applications, data collection in harsh environments with the help of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) appears as a popular approach. However, from a networking and transmission perspective, how unmanned vehicles collaborate with each other and with end IoT devices as well as the propagation characteristics for such data transmissions are less exploited. In this article, we develop a long-range wide-area network (LoRaWAN)-based data collection framework which enables UAV and/or USV-assisted data acquisition in harsh environments. Within this framework, end devices are placed in hard-to-reach locations and data acquisition is performed in an on-demand manner by unmanned vehicles acting as a gateway or peer for end devices (EDs). The framework also includes a step-by-step procedure for data collection and analytics, from parameter configuration to model validation. To reveal the transmission characteristics, we identify three scenarios in a mountainous region in Romania and perform extensive real-life measurements for data collection. Based on the collected datasets, we develop four propagation models and demonstrate that our empirical models outperform the theoretical reference models. Based on the developed empirical models, the coverage of LoRaWAN for any spreading factor (SF) can be estimated with high precision.