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AGROFAM: A DEEP LEARNING-BASED ECOSYSTEM FOR PLANT HEALTH AND SMART FARMING

Alvin Thomas, Sreelakshmi A, Sreelekshmi ., Sooraj R, Nayana Chandran

Abstract


Agriculture faces significant challenges, especially for small-scale farmers, including plant diseases, inefficient crop selection, improper fertilizer use, and limited market access. These issues contribute to low productivity, resource wastage, and financial instability. AgroFam is a deep learning-based system designed to address these problems by integrating plant disease detection, crop recommendation, fertilizer suggestion, and a crop bidding platform. The system uses YOLOv8 for disease detection, achieving 93% mAP and an F1-score of 91.5%, and a Random Forest Classifier for crop recommendations, with 99.3% accuracy. It also analyzes environmental factors for optimal fertilizer recommendations and supports secure marketplace transactions through a MySQL-backed bidding platform. AgroFam’s scalable architecture and intuitive interface provide a comprehensive solu- tion, empowering farmers with data-driven insights for improved productivity and sustainability.


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