International Journal of Science, Engineering and TechnologyAuthors: C.G Anu Chandra, Dinesh Kumar S, I Mohammad Aousaf, Asst.Prof Sumitra Sharma Phurailatpam
Abstract: Efficient water management has become a critical global challenge due to increasing agricultural demands, unpredictable climatic conditions, and limited freshwater resources. Traditional irrigation practices often lead to excessive water usage, reduced crop yields, and higher operational costs. To address these issues, this study presents a Smart Irrigation System that integrates Artificial Intelligence (AI) and the Internet of Things (IoT) to enable intelligent, autonomous, and sustainable water management. In the proposed system, IoT-enabled sensors such as soil moisture sensors, temperature sensors, humidity sensors, and flow meters continuously monitor real-time environmental and soil parameters. These data streams are transmitted to a cloud platform where AI algorithms analyze patterns, predict soil moisture levels, and determine optimal irrigation schedules. The AI module employs machine learning techniques—such as regression models or neural networks—to forecast irrigation needs based on historical and real-time data, crop type, soil condition, and weather predictions. The system automatically actuates irrigation valves using microcontrollers or smart irrigation controllers, ensuring water is supplied precisely when and where it is needed. Additionally, the system provides a user-friendly dashboard or mobile application for remote monitoring, data visualization, and manual override, enhancing farmer engagement and decision-making capabilities.
