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Research Paper | Computer Science and Engineering | Volume 15 Issue 3, March 2026 | Pages: 1256 - 1260 | India
AI Powered Farmer-To-Market Advisory System
Abstract: Farmers often lack access to integrated market intelligence combining price trends, weather variability, and logistics costs, leading to suboptimal selling decisions and post-harvest losses. This study proposes an AI driven farmer to market advisory system that integrates computer- vision based crop identification, real time mandi price retrieval, geolocation enabled transport cost estimation, and storage profitability simulation. The framework analyzes multimodal data to recommend optimal selling markets and timing strategies aimed at maximizing net profit. Experimental validation using real time agricultural price datasets demonstrates improved decision support accuracy and reduced spoilage risk. The proposed system highlights the potential of AI enabled decision platforms to enhance agricultural marketing efficiency and support data driven farm level economic planning.
Keywords: agricultural decision support, profit optimization, multimodal AI, geospatial analytics, and supply chain intelligence
How to Cite?: G. V. Leela Kumari, Marella Suchithra, Matte Rahul, Sriram Balaji, "AI Powered Farmer-To-Market Advisory System", Volume 15 Issue 3, March 2026, International Journal of Science and Research (IJSR), Pages: 1256-1260, https://www.ijsr.net/getabstract.php?paperid=SR26310110408, DOI: https://dx.dx.doi.org/10.21275/SR26310110408