Implementation of Solar Energy for an IoT-Based Agricultural Irrigation and Monitoring System
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Abstract
In Indonesia, there are approximately 27,368,114 households that work as farmers. Generally, farmers use diesel-fueled pumps for rice field irrigation, but in the current era, diesel is becoming scarce. Trials have been conducted with electric pumps, but they are not supported in areas far from residential areas. Therefore, in this research, a pump drive system was created using an induction motor controlled by an ESP32, with sensor integration for monitoring, solar energy as the Power supply, and the BLYNK application for remote monitoring. The results of the study show that solar panels can produce 580.6 Watts of Power in 8 hours, with a maximum Power of 87.4 Watts at 100,000 lux and 35°C. The sensor accuracy is also perfect, with an average error below 2%. The system also successfully regulated automatic irrigation based on soil moisture levels using the Capacitive Soil Moisture v1.2 sensor: the pump turns on when soil moisture is <40% and stops when it is >60%. Scientifically, this research contributes to the development of an intelligent irrigation system based on solar energy and IoT for remote agricultural areas. However, the control system remains static and is not fully adaptive to changing environmental conditions. Therefore, further research is recommended to integrate artificial intelligence methods, such as fuzzy logic or machine learning, to enhance the system's flexibility and performance across diverse soil conditions. With these developments, this system could become an innovative and sustainable agricultural solution in areas without access to PLN electricity.
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