Unlocking the potential : hybrid blockchain and AI-enabled traceability model development and implementation in the dairy industry: proof-of-concept
Malik, Mohit LU
; Mor, Rahul S.
; Gahlawat, Vijay Kumar
and Kumar, Vikas
(2025)
In Transportation Research, Part E: Logistics and Transportation Review
Part E 205 (2026).
- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3289ee91-f501-40cb-b296-a328cc44d36b
- author
- Malik, Mohit
LU
; Mor, Rahul S.
; Gahlawat, Vijay Kumar
and Kumar, Vikas
- publishing date
- 2025-11-14
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Transportation Research, Part E: Logistics and Transportation Review
- volume
- Part E 205 (2026)
- article number
- 104552
- pages
- 21 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:105022011707
- ISSN
- 1366-5545
- DOI
- 10.1016/j.tre.2025.104552
- language
- English
- LU publication?
- no
- id
- 3289ee91-f501-40cb-b296-a328cc44d36b
- date added to LUP
- 2026-02-06 18:17:37
- date last changed
- 2026-02-26 11:16:33
@article{3289ee91-f501-40cb-b296-a328cc44d36b,
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.}},
author = {{Malik, Mohit and Mor, Rahul S. and Gahlawat, Vijay Kumar and Kumar, Vikas}},
issn = {{1366-5545}},
language = {{eng}},
month = {{11}},
publisher = {{Elsevier}},
series = {{Transportation Research, Part E: Logistics and Transportation Review}},
title = {{Unlocking the potential : hybrid blockchain and AI-enabled traceability model development and implementation in the dairy industry: proof-of-concept}},
url = {{http://dx.doi.org/10.1016/j.tre.2025.104552}},
doi = {{10.1016/j.tre.2025.104552}},
volume = {{Part E 205 (2026)}},
year = {{2025}},
}