AgriMedChain-AI: an intelligent blockchain-based agricultural medicine supply chain framework for traceability, counterfeit detection, and sustainable farming

A. Vijay Kumar; Amjan Shaik

doi:10.46481/jnsps.2027.3715

Authors

A. Vijay Kumar [email protected] Department of Computer Science and Engineering, Bharatiya Engineering Science & Technology Innovation University, Gownivaripalli, Gorantla, Andhra Pradesh, India
Amjan Shaik St. Peter’s Engineering College, Hyderabad, Telangana, India

Keywords:

Artificial intelligence, Blockchain, Internet of Things, Counterfeit detection, Agricultural traceability

Abstract

The proliferation of agricultural medicines has supported crop productivity, but counterfeit pesticides, herbicides, fertilizers, and bio-based products, fragmented supply-chain management, and limited transparency remain major concerns. This study proposes AgriMedChain-AI, a framework integrating artificial intelligence (AI), blockchain, and the Internet of Things (IoT) to improve security and transparency in agricultural-medicine supply chains. The architecture uses QR codes for authentication, IoT sensors for real-time logistics data, Hyperledger Fabric and smart contracts for transaction security, and Random Forest and XGBoost models for counterfeit detection, anomaly detection, and risk prediction. A synthetic dataset of 50,000 supply-chain records, including 3,000 counterfeit and 47,000 genuine records, was evaluated. XGBoost achieved 99.48% accuracy, 93.63% precision, 98.00% recall, and a 95.77% F1-score for the counterfeit class. The framework achieved 97.1% traceability integrity and a 95.8% anomaly-detection rate. Transparency increased from 68.5% for the traditional system to 98.3%, while the proposed Hyperledger Fabric implementation achieved 420 transactions per second with an average latency of 0.82 s, a 71.2% reduction relative to the 2.85 s traditional-database baseline. Under the evaluated simulation conditions, the framework improved traceability, authentication, and supply-chain monitoring while supporting an integrated operational performance assessment.

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