Evaluation of capacitance-based soil moisture sensors in IoT based automatic basin irrigation system

Abstract

Abstract A field experiment was carried out at the Research farm, ICAR-Indian Agricultural Research Institute, New Delhi under bare soil and wheat crop to evaluate the performance of capacitance-based soil moisture sensors in an automatic basin irrigation system. Three capacitance-based soil moisture sensors (SMS) were placed at 25%, 50% and 75% of field length at 37.5 cm (SMS-1), 15 cm (SMS-2) and 7.5 cm (SMS-3) soil depth, respectively. An automatic basin irrigation system consists of capacitance-based soil moisture sensors, a check gate at the inlet and a cloud server. The system could be operated from anywhere with a mobile/ web-based application. Irrigation events were scheduled when soil moisture reached up to 40, 30, and 20% of field capacity. A total of nine irrigation events were monitored over three months period. SMSs were evaluated based on performance in terms of quick response, accuracy, robustness and energy consumption. The results showed that the capacitance-based soil moisture sensors quickly responded to moisture changes and successfully sent data at predefined time intervals. The capacitance-based soil moisture sensors successfully schedule irrigation in wheat crop based on the real time soil moisture status and helped to save 72.5 mm water as compared to manual control irrigation system. The soil moisture sensor recorded a 2 to 8% error compared to the gravimetric method. The solar-powered soil moisture sensor worked well with a 4 to 5 hrs solar charge. It was found that the soil moisture sensor was quite robust and easy to handle and requires the least maintenance. The low energy consumption by the sensor makes it suitable to incorporate in a wireless automatic basin irrigation system.