Blockchain-Enabled Supply Chain Traceability System for Food Safety Monitoring

Priya Sharma; Daniel Okonkwo

doi:10.55001/gast.v1i2.67

摘要

Foodborne illness affects an estimated 600 million people annually, yet current supply chain traceability systems require 7-14 days to identify contamination sources during outbreak investigations. We design and deploy a permissioned blockchain platform (FoodChain+) integrating IoT temperature sensors, QR-coded batch labels, and smart contracts for automated compliance verification across a multi-tier supply network spanning farm, processing, distribution, and retail nodes. A six-month pilot with 847 participants across the poultry supply chain in Southeast Asia reduced traceback time from 9.2 days to 4.3 hours and achieved 99.4% data integrity across 2.3 million recorded transactions. Machine learning anomaly detection on sensor data identified 23 temperature excursions and 8 potential cross-contamination events before they reached retail shelves.

作者简介

Priya Sharma Department of Computer Science, Indian Institute of Technology Delhi, New Delhi 110016, India

Priya Sharma is an associate professor at Department of Computer Science, Indian Institute of Technology Delhi, New Delhi 110016, India. Their research focuses on energy systems, with over 47 publications in peer-reviewed journals.
Daniel Okonkwo Food Safety Research Centre, University of Ghana, Accra, Ghana

Daniel Okonkwo is an associate professor at Food Safety Research Centre, University of Ghana, Accra, Ghana. Their research focuses on machine learning, with over 37 publications in peer-reviewed journals.