AN INTELLIGENT AGRICULTURAL FRAMEWORK INTEGRATING AI-DRIVEN ANALYTICS, MACHINE LEARNING MODELS, AND IOT-BASED SENSING NETWORKS FOR REAL-TIME DECISION-MAKING IN PRECISION AGRICULTURE

The fusion of artificial intelligence (AI), machine learning (ML), and Internet of Things (IoT) technologies is transforming modern agriculture by enabling precise, data-driven decision-making. This paper presents an intelligent agricultural framework that combines IoT-based sensing networks, AI-driven analytics, and adaptive ML models to optimize resource usage, enhance yield prediction, and adapt to dynamic environmental conditions in real-time. The framework integrates multi-source data (e.g., soil, weather, crop health), and utilizes edge computing to reduce latency. Experimental results suggest that this approach significantly enhances agricultural efficiency, sustainability, and responsiveness compared to conventional precision agriculture systems.