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@article{186709,
        author = {Sonawane Pranav Digambar and Gholap Vaibhav Santosh and Rathore Yash Suresh and More Om Dnyaneshwar and Punjabi Sonal Pritesh},
        title = {FARMER-TO-FARMER MARKETPLACE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {2057-2059},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186709},
        abstract = {Agriculture remains a vital pillar of the Indian economy, yet farmers still struggle to access fair markets and accurate information. This paper presents an AI-integrated Farmer-to-Farmer Marketplace, an online platform enabling direct trade between farmers for agricultural products, equipment, and services. The system leverages artificial intelligence to predict price trends, recommend optimal selling times, and suggest potential buyers based on regional demand patterns. It also includes real-time weather forecasting, crop advisory systems, and sentiment-based market analysis to support informed decisions. The proposed system uses an agile development approach and a modular architecture that ensures scalability and adaptability. The platform aims to enhance transparency, reduce intermediaries, and increase profitability for rural farmers, thus promoting a data-driven approach to sustainable agriculture.},
        keywords = {AI Prediction System, Digital Marketplace, Farmer-to-Farmer Trade, Smart Agriculture, Predictive Analytics.},
        month = {November},
        }