AGROCRAFT: An Integrated Ml-Driven Crop Recommendation and E-Commerce Framework for Smart Agriculture

Abstract

Indian agriculture grapples with persistent structural challenges—think inefficient crop choices, lack of timely agro environmental data, and a dependency on intermediaries that chips away at farmer profits and long-term sustainability. Enter Agrocraft, this platform integrates machine learning-based crop recommendations with an auction-driven e-commerce marketplace. The machine learning component draws on a comprehensive set of agro-environmental factors—soil nutrients NPK (nitrogen, phosphorus, potassium), pH, rainfall, temperature, humidity—to guide farmers toward crops that maximize yield, resource efficiency, and environmental sustainability. On the market side, Agrocraft’s auction system allows farmers to list their produce and sell it directly, bypassing the traditional middleman and opening up transparent, competitive bidding. This approach not only ensures fairer prices but also gives farmers greater control over their produce and earnings. By merging intelligent crop selection with improved market access, Agrocraft encourages data-driven choices, economic empowerment, and sustainable practices. Initial pilot results indicate notable gains in farmer income and user experience, highlighting Agrocraft’s potential as a scalable solution for the Indian agricultural sector.