Fuzzy Based Irrigation Control System for Indian Subcontinent

Water resource usage should be optimized as there is always a scarcity. This paper aims to provide an efficient way of water using sense and weather data and implementing a fuzzy decision model. An automated intelligent watering system is proposed in this paper using the internet of things and fuzzy logic. The weather data, coupled with Temperature, Relative Humidity, and soil moisture sensor data, is used to decide whether to switch on/off the motor. In-house-created prototypes of ground-moving robots have soil moisture, digital humidity, and temperature sensors implanted in them. The soil moisture sensor is attached to the Rack and pinion mechanism. The soil moisture sensor is pushed into the soil when the pinion rotates. It minimizes the use of sensors by using a distributed sensing method. Based on data obtained from sensors and meteorological information, the system will use this information to decide whether to Switch on/off the sprinkler motor. A fuzzy logic-based system decision is implemented on the input sensor and weather data, and the model will decide to switch on/off the actuator. An accuracy of 97% is achieved. The Android app is used to visualize sensor data, based on which the farmer can manually control the motor.