Enabling Context Aware Tuning of Low Power Sensors for Smart Agriculture

This paper describes an application for the context aware tuning of the data rate of a battery powered LoRaWAN multi-sensor node equipped with sensors measuring soil features like water content, temperature, conductivity, moisture and water table depth. The application aims at saving as much power as possible, granting at the same time the detection and accurate profiling of events localized in time and space (e.g., due to sudden heavy rain). The tuning rules are based on the interplay between the context heterogeneous actors (sensor data, forecasts, current season, irrigation requests) mediated by a Linked Data distribution platform interconnected to multiple private and public networks. An interoperable application is provided, whose components can be easily extended and reused.