Soil-Specific Calibration and Integration of Low-Cost Capacitive Soil Moisture Sensors into a Solar-Powered Sensor Node

Accurate real-time soil moisture monitoring is critical for optimizing water use and ensuring crop health and food security. This study aims to calibrate and integrate low-cost capacitive soil moisture sensors into a solar-powered sensor node for real-time soil moisture monitoring in a loamy sand soil. Three capacitive soil moisture sensors were calibrated in the laboratory under controlled volumetric water content conditions (0–40%) using a constrained linear regression approach. The system was tested in a limited pilot-scale in a drip-irrigated onion field at the IWAD farm, Yagaba (North-East Region, Ghana). The results showed good agreement of the sensor readings with the soil moisture obtained using the gravimetric method (R2 of 0.92–0.94, RMSE of 0.40–0.52%, and MAE of 0.35–0.39%) demonstrating the successful transfer of the calibration functions to field conditions. Soil moisture data was successfully monitored and transmitted from the nodes to a LoRa gateway via LoRaWAN (433 MHz) and from the gateway to a Raspberry Pi edge server via Wi-Fi. Data was stored both locally in SQLite on the Raspberry Pi and on the InfluxDB cloud. These results suggest that the developed system, when extensively validated under field conditions, can be used to support decision-making for data-driven IoT-based irrigation scheduling.