Artículo

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

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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 comprehensive bibliometric and systematic literature review to explore emerging trends, research patterns, and methodologies in integrating BC, IoT, and AI into traceability systems. In the study, 530 documents from the SCOPUS database for bibliometric analysis were examined, alongside a detailed review of 43 selected articles from multiple databases. The findings highlighted a significant increase in research output in recent years, with a dominant focus on agricultural supply chains and SCM. Notably, India and China lead the field in publications and citations. Furthermore, key authors and influential journals significantly contributed to advancing the research. The analysis also revealed a predominance of experimental and hybrid research methodologies, with Ethereum and Hyperledger Fabric emerging as the most widely adopted platforms for system implementations. The study identified critical research trends, including the growing role of AI-driven analytics, the importance of real-time IoT data collection, and the critical need for secure, tamper-proof data provided by BC. However, challenges, such as interoperability, scalability, and standardization, remain hindering the widespread adoption of these technologies. The paper proposes a four-layer conceptual framework for integrating BC, IoT, and AI into future traceability systems, emphasizing their potential to enhance transparency, security, and efficiency across various application areas. The paper concludes by offering directions for future research, highlighting the need for more empirical studies, industry-specific frameworks, and standardization to overcome existing limitations.
Saidu, Yahaya (58672455600); Shuhidan, Shuhaida Mohamed (41762434600); Aliyu, Dahiru Adamu (59515365400); Aziz, Izzatdin Abdul (24314530600); Adamu, Shamsuddeen (58260313700)
Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review
2025
10.1109/ACCESS.2025.3528035
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215121475&doi=10.1109%2fACCESS.2025.3528035&partnerID=40&md5=5fcac263636dd061a6fd3f7f25fbfe61
Universiti Teknologi Petronas, Department of Computer and Information Sciences, Perak Malaysia, Seri Iskandar, 32610, Malaysia; Taraba State University, Department of Computer Science, Jalingo, Nigeria
All Open Access; Gold Open Access
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