A Scalable and Energy-Efficient LoRaWAN-Based Geofencing System for Remote Monitoring of Vulnerable Communities

With the advent of the Internet of Things (IoT), Long-range Wide Area Networks (LoRaWAN), and high-speed internet, the potential to use such technologies for monitoring remote areas with limited cellular coverage is becoming increasingly important. However, existing remote monitoring solutions rely on cellular networks, which often do not exist or are unreliable in remote communities such as oil & gas and mining sites, livestock farms, and some specialized care clinics for monitoring individuals with Alzheimer's disease. Furthermore, existing LoRa-based systems that are geolocation aware used star network topology, which has been proven to be not scalable to cover remote communities due to maintaining a massive volume of routing tables. This paper introduces a LoRaWAN-based geofencing system designed to address the unique challenges faced by these communities, especially areas with limited cellular coverage. The proposed system uses an optimized version of the Echo protocol to enhance the system's reliability, which runs over a mesh network topology that provides a scalable solution for monitoring remote areas. In particular, we developed a geolocation and geofencing alert system tailored to overcome the limitations of cellular coverage in remote areas. Our system utilized LoRaWAN hardware supported by an optimized Echo protocol in a zero-control mesh network to efficiently detect boundary breaches of the monitored subjects such as cattle, patients with Alzheimer's disease, robots mounted with IoT devices and sensors, etc. Experimental results showed that our system outperformed cellular-based systems regarding energy efficiency and scalability.