Published Paper Details:

This paper presents an innovative approach to optimize water usage in agricultural settings. This study explores the integration of Internet of Things (IoT) sensors and artificial intelligence (AI) algorithms to create a dynamic, data-driven irrigation management system. The proposed system utilizes a network of soil moisture sensors, weather stations, and crop-specific data to continuously monitor field conditions. AI algorithms process this real-time data to generate precise irrigation schedules and recommendations, adapting to changing environmental factors and crop water requirements. The paper focuses the system architecture, sensor deployment strategies, and machine learning models employed for decision support. This research contributes to sustainable agriculture practices by offering a scalable solution for efficient water management in farming, addressing the critical challenge of water scarcity in agricultural production.