Analysis of Drip Irrigation Systems Based on the Principle of a Fuzzy Inference Mechanism

Abstract

Nowadays, we observe an increasing need for the efficient use of natural resources, including water. This work examines studies that utilize innovative solutions for optimizing irrigation in agriculture based on fuzzy inference and IoT for drip irrigation. The results of the research show that fuzzy irrigation systems can significantly improve agricultural productivity and water conservation. The fuzzy inference mechanism is explainable, transparent, and adaptable for the user. In the work, we subsequently designed a system that is universal and adaptable to the specific needs of individual growers. This system represents a cost-effective design of an irrigation system using the Arduino Nano microcontroller board, various types of sensors, and fuzzy rules. Based on input values, the result of inference, and defuzzification, an impulse for irrigation intensity is calculated.