Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review
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 var...
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2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10836689/ |
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| author | Yahaya Saidu Shuhaida Mohamed Shuhidan Dahiru Adamu Aliyu Izzatdin Abdul Aziz Shamsuddeen Adamu |
| author_facet | Yahaya Saidu Shuhaida Mohamed Shuhidan Dahiru Adamu Aliyu Izzatdin Abdul Aziz Shamsuddeen Adamu |
| author_sort | Yahaya Saidu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-32b9277d695645349fa54b178124fb13 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-32b9277d695645349fa54b178124fb132025-01-31T00:01:43ZengIEEEIEEE Access2169-35362025-01-0113168381686510.1109/ACCESS.2025.352803510836689Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive ReviewYahaya Saidu0https://orcid.org/0009-0000-8909-8806Shuhaida Mohamed Shuhidan1https://orcid.org/0000-0002-6317-4724Dahiru Adamu Aliyu2https://orcid.org/0009-0009-9803-3604Izzatdin Abdul Aziz3https://orcid.org/0000-0003-2654-4463Shamsuddeen Adamu4https://orcid.org/0009-0008-4015-1723Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, MalaysiaDepartment of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, MalaysiaDepartment of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, MalaysiaDepartment of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, MalaysiaDepartment of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, MalaysiaThe 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.https://ieeexplore.ieee.org/document/10836689/Artificial intelligencebibliometric analysisblockchainInternet of Things (IoT)traceabilitysupply chain and systematic literature review |
| spellingShingle | Yahaya Saidu Shuhaida Mohamed Shuhidan Dahiru Adamu Aliyu Izzatdin Abdul Aziz Shamsuddeen Adamu Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review IEEE Access Artificial intelligence bibliometric analysis blockchain Internet of Things (IoT) traceability supply chain and systematic literature review |
| title | Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review |
| title_full | Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review |
| title_fullStr | Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review |
| title_full_unstemmed | Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review |
| title_short | Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review |
| title_sort | convergence of blockchain iot and ai for enhanced traceability systems a comprehensive review |
| topic | Artificial intelligence bibliometric analysis blockchain Internet of Things (IoT) traceability supply chain and systematic literature review |
| url | https://ieeexplore.ieee.org/document/10836689/ |
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