AgriConnect+: A Multi-Modal AI Framework for Crop Health Analysis, Price Forecasting, and Soil-Aware Recommendation

Abstract

AgriConnect+ is an AI-based decision support system designed to assist farmers in managing crop diseases, price uncertainty, and soil-driven crop selection. The framework integrates deep learning and machine learning techniques to provide three key functionalities: crop disease detection using CNN-based segmentation, crop price prediction through ensemble learning on historical market data, and soil-based crop recommendation using Top-K ranking models. Experimental results show effective disease localization, accurate price forecasting, and reliable crop recommendations. The integrated architecture enables scalable deployment and supports data-driven, sustainable agricultural decision-making.

Code and data availability

The paper describes using publicly available plant leaf image datasets, mandi price data, and soil datasets, but never names them, provides no access URLs, DOIs, or repository identifiers, and offers no author code, models, or supplementary data. All allowed URLs are citations to prior work, not paper-specific assets.

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