AI-Based Irrigation Prediction Using IOT and Machine Learning for Smart Agriculture.

Abstract

Abstract Agriculture is the backbone of many economies, but inefficient irrigation practices lead to water wastage and reduced crop productivity. This paper presents an Artificial Intelligence (AI)-based irrigation prediction system integrated with the Internet of Things (IoT) for smart agriculture. The proposed system collects real-time environmental data such as soil moisture, temperature, humidity, rainfall probability, and water level through IoT sensors. Machine Learning algorithms analyze the collected data and predict the optimal irrigation schedule. The system automatically controls water pumps based on prediction results, reducing water consumption and improving crop yield. Experimental analysis demonstrates that the proposed system can significantly optimize irrigation efficiency while minimizing human intervention. Keywords: Artificial Intelligence, Internet of Things, Smart Agriculture, Machine Learning, Irrigation Prediction, Precision Farming.