Intelligent Agricultural Irrigation System Design And Implementation

Abstract

Water scarcity and inefficient irrigation practices remain critical challenges in agriculture, particularly in arid and semi-arid regions. This thesis presents the development of a smart irrigation system that leverages the Internet of Things (loT) and fuzzy logic control to optimize water usage and promote sustainable agricultural practices. The proposed system integrates low-cost sensors to monitor environmental parameters such as soil moisture, temperature, and humidity in real time. An Arduino-based microcontroller processes these inputs using a fuzzy logic inference system to make intelligent irrigation decisions. The item sues A seme cary me wais designes , sinabling uranian in ing under uncertain conditions and dynamically adjust irrigation duration and frequency. Field-level testing demonstrated that the system can maintain optimal soil moisture levels while reducing water consumption by up to 30% compared to manual irrigation methods. The results confirm that the integration of loT with fuzzy logic provides an effective, scalable, and accessible solution for precision irrigation. This work contributes to the advancement of intelligent farming technologies and offers a practical model for future deployment in water- sensitive agricultural environments.