Analysis comparison, calibration, and application of low-cost soil moisture in smart agriculture based on internet of things

Abstract

The gravimetric method is one of the most accurate for determining soil water content (SWC). Several low-cost sensors have been developed to simplify measuring water content in soil by measuring soil moisture. However, the sensor must be calibrated to determine soil moisture parameters accurately. In this research, comparative analysis, and calibration of resistive and capacitive low-cost sensors were carried out. The calibration method for each sensor uses the gravimetric water content (GWC) and volumetric water content (VWC) methods. Measuring changes in SWC using sensors is performed in real time based on internet of things (IoT). Based on the measurements of the capacitive, resistive type 1, and resistive type 2 sensors with three repetitions, the linear regression R² values were obtained at 0.980, 0.827, and 0.942, respectively. Furthermore, a stability test is carried out to see how stable the sensor is when making measurements over a long period. The result is that the capacitive, resistive type 1, and resistive type 2 sensors have errors 1.971×10^-4, 7.001×10^-4, and 6.270×10^-4. Based on the results obtained, capacitive sensors have the highest level of accuracy and stability. Furthermore, capacitive sensors are applied to IoT-based agriculture with long range (LoRa) as communication data.