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@article{189492,
author = {Swapnil G. Gaikwad and Tanvi A. Pawar and Surbhi S. Shinde and Proff. Sandhya E. Aghav},
title = {CropConnect AI: An AI-Driven Farmer-to-Farmer Marketplace with Integrated Advisory and Predictive Analytics},
journal = {International Journal of Innovative Research in Technology},
year = {2025},
volume = {12},
number = {7},
pages = {6437-6442},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=189492},
abstract = {Agriculture continues to face significant challenges related to unfair market pricing, dependency on intermediaries, lack of timely expert guidance, and limited access to real-time information. Although several digital platforms attempt to support farmers, most of them operate in isolation and fail to provide a unified solution. This paper presents Crop Connect AI, an artificial intelligence–driven web platform designed to enable direct farmer-to-farmer and farmer-to-buyer interaction while integrating essential agricultural services. The proposed system combines machine learning–based price prediction, image-based crop disease detection, retrieval-augmented generation (RAG) for intelligent advisory, and real-time weather and market analysis. By eliminating intermediaries and offering data-driven insights, Crop Connect AI improves transparency, decision-making, and operational efficiency for farmers. The system demonstrates the potential to enhance agricultural trade, optimize resource utilization, and support sustainable farming practices through an integrated and user-centric digital ecosystem.},
keywords = {Smart Agriculture, Farmer Marketplace, Artificial Intelligence, Machine Learning, RAG, Price Prediction, Crop Advisory},
month = {December},
}
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