Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review

Saidu, Yahaya and Shuhidan, Shuhaida Mohamed and Aliyu, Dahiru Adamu and Abdul Aziz, Izzatdin and Adamu, Shamsuddeen (2025) Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review. IEEE Access, 13. 16838 – 16865. ISSN 21693536

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Abstract

The need for sophisticated traceability systems has become essential in increasingly complex and globalized supply chains. The convergence of Blockchain (BC), Internet of Things (IoT), and Artificial Intelligence (AI) technologies offers promising solutions to enhance traceability systems across various sectors, particularly supply chain management (SCM). This paper presents a bibliometric and systematic literature review (SLR) to examine trends, research patterns, and methodologies in integrating BC IoT and AI into traceability systems. Bibliometric analysis of 530 documents from SCOPUS (2014-2024) identified key trends, while the SLR, conducted across multiple databases following PRISMA guidelines, refined the dataset to 43 peer-reviewed studies based on inclusion criteria. Recent research output has notably increased, focusing on agricultural supply chains and SCM, with India and China leading in publications. The analysis shows a predominance of experimental and hybrid methodologies, using Ethereum and Hyperledger Fabric as key platforms. Key trends include AI-driven analytics, real-time IoT data collection, and the need for secure, tamper-proof data by BC. However, interoperability, scalability, and standardization challenges hinder adoption. The paper proposes a four-layer framework for integrating BC, IoT, and AI to improve transparency, security, and efficiency and highlights the need for more empirical studies, industry-specific frameworks, and standardization to overcome existing limitations. © 2025 The Authors.

Item Type: Article
Impact Factor: Cited by: 6; All Open Access, Gold Open Access
Uncontrolled Keywords: Bibliographies; Blockchain; Supply chains; Artificial intelligence technologies; Bibliometric; Bibliometrics analysis; Block-chain; Chain management; Emerging trends; Internet of thing traceability system; Research methodologies; Systematic literature review; Traceability systems; Supply chain management
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 08 Jul 2025 16:22
Last Modified: 08 Jul 2025 16:22
URI: http://scholars.utp.edu.my/id/eprint/38910

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