AI-Driven Predictive Irrigation: Revolutionizing Agricultural Water Management

Abstract

Water scarcity and inefficient irrigation practices pose significant challenges to modern agriculture, especially in arid regions. Traditional irrigation methods often result in excessive water consumption, higher operational costs, and lower crop yields. This research paper investigates the potential of Artificial Intelligence (AI) in predictive irrigation systems, emphasizing how AI algorithms can optimize irrigation schedules by analyzing factors such as weather forecasts, soil moisture levels, and crop water requirements. By leveraging real-time and historical data, AI-driven irrigation systems improve water efficiency, conserve resources, and support sustainable farming practices. This paper reviews existing AI techniques in predictive irrigation, discusses their advantages and challenges, explores future developments, and examines the broader impact of AI on agricultural water management.