Development of Smart Farming Control System based on Tsukamoto Fuzzy Algorithm

Smart farming is one of the most effective methods to increase productivity. Smart farming is changing the face of conventional agriculture methods by making them convenient, cost-effective, and energy-efficient, as well as minimizing crop waste. Smart farming reduces the physical labor produced by humans, such as irrigation, fertilization, application of pesticides, and many more. Smart farming is used for monitoring and determining the current pH level, air temperature, soil temperature, and humidity in agricultural land. With this method, the plants will have always good condition to support them. Moreover, the production of agricultural land will be increased. This paper proposes the development of smart farming monitoring system, which uses ESP32 for the microcontroller, 4 sensors for monitoring the input data, and an actuator for activating the water pump. This system is supported by Tsukamoto Fuzzy Logic based on the norms of human resources with the criteria that have been determined. The initial step is the fuzzification process which includes four input parameters (pH sensor, humidity sensor, air temperature sensor, and soil temperature sensor) used as reference values to determine defuzzification. This process is carried out through all rules. The next step is to determine the defuzzification process, which is to determine the output produced by the actuator in the water pump to release the water. The result of this paper is to produce a system that can help farmers monitor environment data from each sensor in real time and help the farmers watering the plant automatically.