Blockchain-based intelligent tracing of food grain crops from production to delivery

Abstract

Traceability in the food industry has become essential to ensuring safety, quality, and regulatory compliance. Traditional traceability methods often lack transparency, efficiency, and security, leading to challenges in verifying product quality and adherence to health regulations. This paper addresses these challenges by presenting a unique blockchain-based framework/system to enhance the traceability of the food grain. Integrating sensors, Raspberry Pi units, IPFS, and Ethereum Blockchain creates a transparent and auditable supply chain, empowering every participant within the supply chain to verify quality and adherence to healthful regulations. The suggested framework combines machine learning (ML) with blockchain technology. ML is responsible for distinguishing between valid and invalid data within the agri-food supply chain in this setup. At the same time, blockchain ensures that only valid data is stored, maintaining its security and privacy. This is crucial for consumer trust and enabling regulatory bodies to conduct efficient online inspections and ensure adherence to best practices. Finally, the proposed system is evaluated using various performance metrics. In terms of scalability, as the volume of data transactions increases, the system’s scalability improves. The framework shows faster transaction commitments, reduced propagation delays, higher throughput, and lower latency with higher transaction volumes. Additionally, the security analysis confirms that the proposed system effectively addresses critical security and privacy concerns, including confidentiality, data integrity, availability, non-repudiation, and protection against cyber-attacks. The proposed blockchain-based traceability framework for food grains has shown substantial possibility in reducing fraud and improving transparency and consumer trust.