A Blockchain and AI-Powered Digital Marketplace for Optimizing Agricultural Trade Efficiency and Farmer Empowerment

Authors

  • Dr. Arthy Rajakumar Associate Professor, Department of Information Technology, Kamaraj College of Engineering and Technology, Madurai, Tamilnadu, India. Author
  • Janavarshini G UG Student, Department of Information Technology, Kamaraj College of Engineering and Technology, Madurai, Tamilnadu, India. Author
  • Hemadharshini R UG Student, Department of Information Technology, Kamaraj College of Engineering and Technology, Madurai, Tamilnadu, India. Author
  • Nooril Afina T UG Student, Department of Information Technology, Kamaraj College of Engineering and Technology, Madurai, Tamilnadu, India. Author

DOI:

https://doi.org/10.47392/IRJASH.2025.016

Keywords:

Agricultural Trade, Smart Marketplace, Blockchain, Artificial Intelligence, Recommendation System, Fraud Detection, Machine Learning, Dynamic Pricing, NLP, Secure Transactions, Direct Market Access, Regression Models, Anomaly Detection, Supply Chain Optimization

Abstract

This paper addresses inefficiencies in agricultural trade resulting from intermediaries together with restricted direct market participation by farmers and volatile market prices. This paper proposes "A Blockchain and AI-Powered Digital Marketplace for Optimizing Agricultural Trade Efficiency and Farmer Empowerment" a mobile application that applies both Blockchain technology and artificial intelligence to directly link farmers with buyers while securing fair prices and full market access. Farmers can register, list, and manage their products, and buyers can find products by proximity to receive the supply. The application provides dynamic pricing based on demand and seasonality, multilingual accessibility through NLP, and blockchain for secure transactions. Moreover, farmers get real-time order notifications which help them arrange for delivery through self-pickup, courier, or postal service. The proposed system incorporates linear regression and random forest regression algorithms for pricing optimization, matrix factorization and SVD for recommendation systems, and supervised learning and anomaly detection for fraud detection contribute to a more productive, efficient and profitable agricultural ecosystem.

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Published

2025-03-04