Malik, M., Mor, R. S., Gahlawat, V. K. and Kumar, V. (2025) Unlocking the potential: hybrid blockchain and AI-enabled traceability model development and implementation in the dairy industry – proof-of-concept. Transportation Research, Part E: Logistics and Transportation Review. 205(Januar), pp. 1-21. 1366-5545.
- Information
Information
Abstract:
Conventional traceability systems without real-time information transmission are susceptible to tampering. In contrast, blockchain and artificial intelligence (AI)-enabled traceability models offer transparency and accountability, given their decentralized nature and immutability. This research conceptualizes and develops a hybrid blockchain and AI-enabled traceability (prototype) model and implements it in the dairy industry. The study includes a collaborative research methodology, including a literature review to analyze the existing traceability solutions, identify data entry points, select model requirements, and deploy smart contracts, decentralized applications (Dapps) and Web3 technologies to develop and validate the proposed model via Testnet. The findings present the user interface developed as a prototype traceability model and its characteristics, such as transparency, decentralized nature, and immutability, followed by practical validation. The post-implementation data analysis highlighted the security, privacy, smart contract validation rules, and comparative insights, as well as the alignment of the theoretical model with practical applications using Web3 technologies. This research contributes to the literature on hybrid blockchain and AI-enabled traceability, highlighting the potential for exploring opportunities in the food industry.
Additional Information:
© 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Uncontrolled Keywords:
/dk/atira/pure/sustainabledevelopmentgoals/industry_innovation_and_infrastructure
Creators:
Malik, M., Mor, R. S., Gahlawat, V. K. and Kumar, V.
Date:
8 November 2025
Date Type:
Acceptance
Page Range:
pp. 1-21
Journal or Publication Title:
Transportation Research, Part E: Logistics and Transportation Review
Volume:
205
Number:
Januar
Number of Pages:
2298378
Language:
English
ISSN:
1366-5545
Status:
Published / Disseminated
Refereed:
Yes
![]() |
