Intelligent Water Management System Utilizing AI for Precision Agriculture

Water scarcity is a growing concern, particularly in agriculture, where efficient water management is essential for sustainability and crop yield. This work presents an AI-based irrigation management system aimed at optimizing water utilization through the analysis of real-time soil moisture data, meteorological forecasts, and crop-specific water needs. The system employs IoT-enabled soil sensors and predictive machine learning algorithms to dynamically modify irrigation schedules, thereby substantially minimizing water waste and optimizing crop output. The suggested approach amalgamates several data sources and machine learning methodologies to provide a fully automated and adaptive irrigation system tailored to the distinct requirements of each crop type and growth phase. Experimental findings demonstrate significant enhancements in water efficiency and productivity, underscoring the promise of AI and IoT in enhancing precision agriculture. This study offers a scalable and sustainable methodology for agricultural water management, aiding global initiatives in water conservation and food security enhancement.