Authors : Kayathri Devi M.; Adhifa S.; Guru Sangaran V.; Khatheeja Fazleeena A.

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/bdr2chh8

Scribd : https://tinyurl.com/2ewkd8kp

DOI : https://doi.org/10.38124/ijisrt/26apr709

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The agricultural sector is an important one which plays a significant role in economic development and sustainabil- ity of the developing nations such as India. Nevertheless, farmers still have to struggle with significant issues connected with price fluctuations, absence of direct market access, reliance on inter- mediaries, and insufficient knowledge about digital technologies. These problems usually lead to low profits and inefficient trade of agriculture. The proposed paper is titled Intelligent Agriculture Trade Platform, which is a sophisticated AI-based e-commerce platform that will help farmers and consumers connect the gap in their transactions by allowing direct and transparent transactions. The platform combines machine learning algorithms to predict crop prices, analyze the demand, and provide personalized product recommendations, allowing farmers to make valuable decisions and earn the maximum profits. Moreover, the system has effective security features such as the use of Optical Character Recognition (OCR)-based KYC verification, face authentication and fraud detection technologies to facilitate the secure and dependable transactions. Modern web technologies are used in the development of the platform based on React.js as a frontend, Flask as APIs and MySQL as a database manager, which guarantees scalability and efficiency. The offered system will not only increase the level of transparency and eradicate the middlemen but also foster a sustainable digital agricultural ecosystem. Experimental analysis shows that experimental systems have a better pricing, less fraud risk and user satisfaction.

Keywords : Agriculture, Artificial Intelligence, E-commerce, Machine Learning, Predicting Prices, Detecting Fraud, KYC Verification, Digital Marketplace.

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