Smart Crop Advisory System improves crop selection and fertilizer application for smallholder farmers, suggesting more efficient practices.
This paper presents the Smart Crop Advisory System (SCAS), a hybrid AI-based web platform designed to improve crop selection and fertilizer application decisions for smallholder farmers. The system integrates a Random Forest machine learning classifier with a rule-based fertilizer advisory engine to deliver real-time, context-aware recommendations. It combines soil nutrient inputs (N, P, K, pH) with live weather data retrieved via API to generate accurate crop predictions and nutrient guidance. Built using Python, Flask, and scikit-learn, the system achieves high accuracy (98%+) and low latency. The platform supports multilingual access (English, Hindi, Marathi), improving accessibility and usability. SCAS demonstrates significant potential in enhancing agricultural efficiency, reducing fertilizer misuse, and supporting sustainable farming practices.
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Dhas et al. (2026) studied this question.
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