A LoRa based Ultra-Low-Power Network for Distributed Environmental Sensing in Remote Offline Areas

Assessing and predicting the behavior of Arctic and mountainous ecosystems under changing climate conditions remains a challenge that requires highly spatiotemporally resolved observations of numerous above- and below-ground hydro-biogeochemical processes. Wireless environmental sensors represent a promising venue for cost-efficient, large-scale monitoring, but remote field sites often lack the network connectivity and bandwidth for real-time data transmission. Wireless Sensor Networks (WSN) can be used to aggregate sensor data in a central node in the field. Yet, current WSN technologies are often characterized by high power consumption, short range, lack of reliability, and a dependency on cloud connectivity.

This research presents a novel Low-Power Wide-Area Network (LPWAN) stack for remote, disconnected field sites. The system is based on a LoRa physical network layer, which guarantees long range transmissions and widely available hardware. The network protocol differs from standard LoRaWAN technology because it uses synchronized transmitters and receivers with single channel radios and Frequency Hopping Spread Spectrum transmissions. This allows low-cost, ultra-low-power receivers, so multiple redundant base stations can be spread over a field site, guaranteeing data integrity. In these edge devices, data is aggregated and analyzed. Sensor data can be accessed in the field, but analytics can be uploaded over a low bandwidth connection (e.g., satellite link), providing live status updates of field conditions.

This work presents the implementation of this communication technology in our Distributed Temperature Profiling (DTP) system, which measures vertically resolved soil or snow temperatures with an unprecedented spatiotemporal resolution at several field sites in mountainous and Arctic regions. We present an assessment of the power consumption, battery lifetime, and range for different network configurations based on our initial field tests. The WSN provides reliability and usability for distributed sensor systems in the field through data centralization with redundancy, while enabling new features like edge computing for remote analytics.