Fuzzy Logic Based Intelligent Control for Irrigation Timing

Abstract

Effective water management in agriculture continues to be a significant concern, particularly in areas where sustainable irrigation is crucial. This research introduces a fuzzy logic-based control system designed for reducing water consumption while ensuring ideal soil moisture levels. This method integrates soil moisture, temperature, humidity, and solar irradiance into a fuzzy inference model that autonomously controls irrigation time. In contrast to traditional threshold-based approaches, the fuzzy system renders adaptive choices despite ambiguous sensor input. Simulations in MATLAB utilizing realworld scenarios were conducted to evaluate system performance. The results indicate enhanced water efficiency, improved adaptability to environmental changes, and increased soil moisture stability relative to traditional methods. The study proves the efficacy of fuzzy logic as a valuable instrument for intelligent and sustainable irrigation.