SMART AI FARMING: AN INTEGRATED WEB-BASED DECISION- SUPPORT SYSTEM USING MACHINE LEARNING AND DEEP LEARNING

This paper has described Smart AI Farming, a web-based prototype that combines CNN-based leaf-image classification with a modular decision-support workflow. The implementation uses Flask, TensorFlow/Keras, OpenCV, and structured data sources to connect image upload, preprocessing, prediction, result display, and recommendations. The paper successful functional test cases for the principal application flow.   Further extensions may incorporate IoT sensors, drone or satellite imagery, expert advisory services, and links to public agricultural schemes. Security hardening, usability studies with intended users, and controlled field trials are necessary steps toward a dependable deployment.

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