Towards a Human-Centric Industry 5.0 Enabled by the Convergence of Artificial Intelligence, Internet of Things, and Blockchain

Document Type : Review article

Author

Department of Electrical Engineering,University of Guilan,Rasht,guilan,Iran

10.22091/jdaid.2026.14749.1025

Abstract

Industry 5.0 envisions a transformative industrial paradigm that goes beyond mere automation, emphasizing human-centricity, sustainability, and resilience. The convergence of Artificial Intelligence (AI), Internet of Things (IoT), and Blockchain forms a powerful technological foundation to achieve this vision, enabling intelligent, interconnected, and secure industrial operations. In this paper, we propose a comprehensive conceptual architecture for integrating these three technologies, facilitating seamless interaction between humans, machines, and decentralized systems. We conduct a systematic review of the existing literature, examining design patterns, practical use cases, adoption barriers, and key challenges. Additionally, we analyze real-world industrial implementations to extract insights, lessons learned, and best practices. Our findings highlight critical technical, governance, and scalability issues, including interoperability, data privacy, regulatory compliance, and infrastructure limitations. To address these challenges, we present a multiphase strategic roadmap for the deployment and adoption of AI–IoT–Blockchain convergence in human-centric industrial environments. Finally, we discuss emerging research directions, such as post-quantum blockchains, federated learning, autonomous economic agents, and resilient cyber-physical systems. Our analysis indicates that while the convergence of these technologies holds transformative potential for Industry 5.0, practical and scalable adoption requires careful system design, iterative prototyping, and robust policy frameworks. This study provides a structured reference for researchers, practitioners, and policymakers seeking to advance human-centric, sustainable, and technologically empowered industrial systems.

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References

Alharbi, S., Attiah, A., & Alghazzawi, D. (2022). Integrating blockchain with artificial intelligence to secure IoT networks: Future trends. Sustainability, 14(23), 16002. https://doi.org/10.3390/su142316002
Aounzou, Y., Boulaalam, A., & Kalloubi, F. (2025). Convergence of blockchain, IoT, and machine learning: Exploring opportunities and challenges – A systematic review. International Journal on Smart Sensing and Intelligent Systems, 18(1). https://doi.org/10.2478/ijssis-2025-0002
Aravinth, S. S. (2025). Unleashing the power of data and security by integrating deep learning and blockchain in smart city infrastructure development–A future perspective. In Deep Learning and Blockchain Technology for Smart and Sustainable Cities (pp. 20–42). Auerbach Publications. https://doi.org/10.1201/9781003476047
Atlam, H. F., Azad, M. A., Alzahrani, A. G., & Wills, G. (2020). A review of blockchain in Internet of Things and AI. Big Data and Cognitive Computing, 4(4), 28. https://doi.org/10.3390/bdcc4040028
Azad, U., Behera, B. K., Song, H., & Farouk, A. (2025). A blockchain-based quantum binary voting for decentralized IoT towards Industry 5.0. arXiv:2503.20247. https://doi.org/10.48550/arXiv.2503.20247
Bagherabad, M. B., Rivandi, E., & Mehr, M. J. (2026). Machine learning for analyzing the effects of various factors on business economics. Applied Decision Analytics, 2(1), 41-54.
Bevilacqua, C., Vitiello, G., Sebillo, M. M. L., Provenzano, V., Sohrabi, P., Hamdy, N., Trapani, F., & Pizzimenti, P. (2025). A multidisciplinary approach to plan ECOsystem services for cities in transition. In Proceedings of the 16th Biannual Conference of the Italian SIGCHI Chapter (pp. 1-1). https://doi.org/10.1145/3750069.3757877
Bhumichai, D., Smiliotopoulos, C., Benton, R., Kambourakis, G., & Damopoulos, D. (2024). The convergence of artificial intelligence and blockchain: The state of play and the road ahead. Information, 15(5). https://doi.org/10.3390/info15050268
Choi, N., & Kim, H. (2024). Technological convergence of blockchain and artificial intelligence: A review and challenges. Electronics, 14(1), 84. https://doi.org/10.3390/electronics14010084
Conoscenti, M., Vetro, A., & De Martin, J. C. (2016). Blockchain for the Internet of Things: A systematic literature review. In Proceedings of the IEEE/ACS 13th International Conference on Computer Systems and Applications (AICCSA). https://doi.org/10.1109/AICCSA.2016.7945805
Fraga-Lamas, P., & Fernandez-Carames, T. M. (2019). A review on blockchain technologies for an advanced and cyber-resilient automotive industry. IEEE Access, 7, 17578–17598. https://doi.org/10.1109/ACCESS.2019.2895302
Gadekallu, T. R., Pham, Q.-V., Nguyen, D. C., Maddikunta, P. K. R., Deepa, N., Pathirana, P. N., Zhao, J., & Hwang, W.-J. (2021). Blockchain for edge of things: Applications, opportunities, and challenges. IEEE Internet of Things Journal, 9(2), 964–988. https://doi.org/10.1109/JIOT.3119639
Ghaderi, Y., & Ghaderi, M. R. (2025). Navigating the future of smart cities: Addressing IoT challenges through blockchain solutions. Information Systems and Smart City, 5(1), 2334. https://doi.org/10.59400/issc2334
Heidari, S., Hashemi, S., Khorsand, M. S., Daneshfar, A., & Jazayerifar, S. (2024). Towards standardized regulations for blockchain smart contracts: Insights from Delphi and SWARA analysis. Amity Journal of Management, XI(II), 1-15. https://doi.org/10.31620/AJM.1121
Jahid, A., Alsharif, M. H., & Hall, T. J. (2023). The convergence of blockchain, IoT and 6G: Potential, opportunities, challenges and research roadmap. Journal of Network and Computer Applications, 217, 103677. https://doi.org/10.1016/j.jnca.2023.103677
Karizaki, M. S., Gnesdilow, D., Puntambekar, S., & Passonneau, R. J. (2024, July). How well can you articulate that idea? Insights from automated formative assessment. In International Conference on Artificial Intelligence in Education (pp. 225-233). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-64299-9_16
Khan, I. U., Al-Hammadi, M. H., & Ghafoor, A. (2025). Integrating AI, blockchain, and edge computing for zero-trust systems. Journal of Smart IoT Security (pre-print).
Leng, J., Chen, Z., Huang, Z., Zhu, X., Su, H., Lin, Z., & Zhang, D. (2022). Secure blockchain middleware for decentralized IIoT towards Industry 5.0: A review of architecture, enablers, challenges, and directions. Machines, 10(10), 858. https://doi.org/10.3390/machines10100858
Luo, X., & Mahdjoubi, L. (2024). Towards a blockchain- and machine-learning-based framework for decentralised energy management. Energy and Buildings, 303, 113757. https://doi.org/10.1016/j.enbuild.2023.113757
Mololoth, V. K., Saguna, S., & Åhlund, C. (2023). Blockchain and machine learning for future smart grids: A review. Energies, 16(1), 528. https://doi.org/10.3390/en16010528‏
Nasiri, S., Shahabi, S., Shafiesabet, A., Talebbeidokhti, M., & Behineh, E. A. (2026). Cybersecurity in action: Unraveling the effects of individual, social, and organizational determinants. Tehnički glasnik, 20(2),1-10, https://doi.org/10.31803/tg-20240627004731
Nguyen, T., Nguyen, H., & Gia, T. N. (2024). Exploring the integration of edge computing and blockchain IoT: Principles, architectures, security, and applications. Journal of Network and Computer Applications, 226, 103884. https://doi.org/10.1016/j.jnca.2024.103884
Nikzat, P. (2025). Review of Artificial Intelligence (AI) revolution and strategic competitive advantage in business and management. American Journal of Industrial and Business Management, 15, 1685-1699. https://doi.org/10.4236/ajibm.2025.1511088
Pezeshgi, A., Naeimi, M., & Pezeshgi, Q. (2025). Buying on impulse in the age of AI: Mechanisms, evidence, and moral dilemmas. Evidence and Moral Dilemmas. https://dx.doi.org/10.2139/ssrn.5402344
Rajawat, A. S., Bedi, P., Goyal, S. B., Shaw, R. N., Ghosh, A., & Aggarwal, S. (2022). AI and blockchain for healthcare data security in smart cities. In AI and IoT for Smart City Applications (pp. 185-198). Springer Nature Singapore.‏https://doi.org/10.1007/978-981-16-7498-3_12
Rehman, A., Abbas, S., Khan, M. A., Ghazal, T. M., Adnan, K. M., & Mosavi, A. (2022). A secure Healthcare 5.0 system based on blockchain technology entangled with federated learning technique. Computers in Biology and Medicine, 150, 106019. https://doi.org/10.1016/j.compbiomed
Rejeb, A., Rejeb, K., Zrelli, I., & Süle, E. (2025). Industry 5.0 as seen through its academic literature: An investigation using co-word analysis. Circular Economy and Sustainability. https://doi.org/10.1007/s43615-025-00570-y
Rivandi, E. (2026). FinTech and the level of its adoption in different countries around the world. Management Science Advances, 1-17. https://doi.org/10.31181/msa33
Sait, S. A., & Vijesh, P. V. (2025). The role of AI, IoT and blockchain in enabling workplace sustainability and efficiency—An empirical analysis. Journal of Emerging Markets and Management, 1(2), 66–80. https://doi.org/10.63385/jemm.v1i2.159
Sandner, P., Gross, J., & Richter, R. (2020). Convergence of Blockchain, IoT, and AI. Frontiers in Blockchain, 3, 522600. https://doi.org/10.3389/fbloc.2020.522600
Singh, N., Singh, S., & Singh, S. J. (2020). Convergence of blockchain and artificial intelligence in IoT: A security analysis. Sustainable Cities and Society, 62. https://doi.org/10.1016/j.scs.2020.102387
Sizan, N. S., Dey, D., Layek, M. A., et al. (2025). Evaluating blockchain platforms for IoT applications in Industry 5.0: A comprehensive review. Blockchain Research and Applications, 100276. https://doi.org/10.1016/j.bcra.2025.100276
Taherdoost, H. (2022). Blockchain technology and artificial intelligence together: A critical review on applications. Applied Sciences, 12(24), 12948. https://doi.org/10.3390/app122412948
Tyagi, A. K., Tripathi, K., Kukreja, S., Tiwari, S., & U., A. S. (2024). Blockchain enabled artificial intelligence for Industry 5.0: Vision, challenges and opportunities. Journal of Autonomous Intelligence, 7(5). https://doi.org/10.32629/jai.v7i5.1479
Zhang, Z., Song, X., Liu, L., Yin, J., Wang, Y., & Lan, D. (2021). Recent advances in blockchain and artificial intelligence integration: Feasibility analysis, research issues, applications, challenges, and future work. Security and Communication Networks, 2021, 1–15. https://doi.org/10.1155/2021/9991535
Journal of Data Analytics and Intelligent Decision-making
Volume 1, Issue 4
January 2026
Pages 32-49

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