Edge AI-Based Smart Agriculture System

This project presents an Edge AI Based Smart Agriculture System designed to improve farming through real-time monitoring and intelligent decision-making. The proposed solution combines Edge AI, IoT devices, and machine learning techniques to collect and process information from soil moisture, temperature, humidity, pH, and NPK sensors. Since data is analysed locally at the edge, the system can respond more quickly, reduce dependence on continuous internet connectivity, and provide timely recommendations for farm management. The developed system also includes an automatic irrigation mechanism that supplies water only when soil conditions require it. This approach helps conserve water, lowers unnecessary energy consumption, and minimizes human intervention. In addition to field monitoring, the system incorporates a market analysis feature that estimates crop price trends and supports farmers in selecting suitable crops and planning the best time to sell their produce. Combining environ-mental monitoring with market-based insights enables more informed agricultural decisions. The proposed model is designed to be cost-effective, practi-cal, and suitable for farms of different sizes. By integrating sensor-based monitoring, intelligent data processing, au-tomated irrigation, and market forecasting into a single platform, the system aims to improve resource utilization, increase crop productivity, and enhance farmers’ income. This work demonstrates the potential of Edge AI to support efficient, sustainable, and technology-driven agricultural practices while addressing the growing need for smart farming solutions.

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