Volume 13 , Issue 2 , PP: 52-61, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
Fausto Vizcaino Naranjo 1 * , Jorge L. Acosta Espinoza 2 , Silvio Machuca Vivar 3
Doi: https://doi.org/10.54216/FPA.130205
The rapid expansion of the Internet of Things (IoT) has ushered in an era of unprecedented data generation, offering transformative potential across industries. Yet, this vast data landscape brings forth challenges related to security, privacy, trust, and intelligent data analysis. In response to these challenges, the fusion of blockchain technology and artificial intelligence (AI) within IoT ecosystems has emerged as a promising solution. This paper embarks on a comprehensive exploration of this fusion, delving into its opportunities and challenges. We provide an overview of IoT's evolution, blockchain technology's fundamental principles, and the significance of AI in data analysis and decision-making. Our focus lies in elucidating how the integration of blockchain fortifies data security, trust, and transparency in IoT applications, while AI augments data analysis, predictive maintenance, and automation. Furthermore, we discuss the challenges and considerations that accompany the integration of AI and blockchain in IoT environments, including scalability, privacy concerns, interoperability, and ethical considerations. By examining the intricate interplay of these technologies, this paper contributes to a deeper understanding of how the fusion of blockchain and AI can usher in a new era of secure, intelligent, and efficient IoT practices.
Fusion, Blockchain, AI , Internet of Things , Enhanced Practices , IoT Ecosystem, Trust , Edge Computing , Privacy , Interoperability.
[1] Tsang, Y. P., Wu, C. H., Ip, W. H., & Shiau, W. L. (2021). Exploring the intellectual cores of the blockchain–Internet of Things (BIoT). Journal of Enterprise Information Management, 34(5), 1287-1317.
[2] Firouzi, F., Jiang, S., Chakrabarty, K., Farahani, B., Daneshmand, M., Song, J., & Mankodiya, K. (2022). Fusion of IoT, AI, edge–fog–cloud, and blockchain: Challenges, solutions, and a case study in healthcare and medicine. IEEE Internet of Things Journal, 10(5), 3686-3705.
[3] A. M.Ali and A. Abdelhafeez, “DeepHAR-Net: A Novel Machine Intelligence Approach for Human Activity Recognition from Inertial Sensors”, SMIJ, vol. 1, Nov. 2022.
[4] Asif, R., & Hassan, S. R. (2023). Exploring the confluence of IoT and metaverse: Future opportunities and challenges. IoT, 4(3), 412-429.
[5] Javaid, M., Haleem, A., Singh, R. P., Khan, S., & Suman, R. (2021). Blockchain technology applications for Industry 4.0: A literature-based review. Blockchain: Research and Applications, 2(4), 100027.
[6] Singh, S. K., Rathore, S., & Park, J. H. (2020). Blockiotintelligence: A blockchain-enabled intelligent IoT architecture with artificial intelligence. Future Generation Computer Systems, 110, 721-743.
[7] Younan, M., Houssein, E. H., Elhoseny, M., & Ali, A. A. (2020). Challenges and recommended technologies for the industrial internet of things: A comprehensive review. Measurement, 151, 107198.
[8] Abdel-Basset, M., Alrashdi, I., Hawash, H., Sallam, K., & Hameed, I. A. (2023). Towards Efficient and Trustworthy Pandemic Diagnosis in Smart Cities: A Blockchain-Based Federated Learning Approach. Mathematics, 11(14), 3093.
[9] Bhattacharya, P., Bodkhe, U., Zuhair, M., Rashid, M., Liu, X., Verma, A., & Kishan Dewangan, R. (2021). Amalgamation of blockchain and sixth‐generation‐envisioned responsive edge orchestration in future cellular vehicle‐to‐anything ecosystems: Opportunities and challenges. Transactions on Emerging Telecommunications Technologies, e4410.
[10] Gehlot, A., Malik, P. K., Singh, R., Akram, S. V., & Alsuwian, T. (2022). Dairy 4.0: Intelligent Communication Ecosystem for the Cattle Animal Welfare with Blockchain and IoT Enabled Technologies. Applied Sciences, 12(14), 7316.
[11] Chakraborty, C., Pani, S., Ahad, M. A., & Xin, Q. (Eds.). (2022). Implementation of Smart Healthcare Systems Using AI, IoT, and Blockchain. Academic Press.
[12] Rejeb, A., Rejeb, K., Appolloni, A., Jagtap, S., Iranmanesh, M., Alghamdi, S., ... & Kayikci, Y. (2023). Unleashing the power of internet of things and blockchain: A comprehensive analysis and future directions. Internet of Things and Cyber-Physical Systems.
[13] Jagatheesaperumal, S. K., Rahouti, M., Ahmad, K., Al-Fuqaha, A., & Guizani, M. (2021). The duo of artificial intelligence and big data for industry 4.0: Applications, techniques, challenges, and future research directions. IEEE Internet of Things Journal, 9(15), 12861-12885.
[14] Al-Doghman, F., Moustafa, N., Khalil, I., Tari, Z., & Zomaya, A. (2022). AI-enabled secure microservices in edge computing: Opportunities and challenges. IEEE Transactions on Services Computing.
[15] Chang, L., Zhang, Z., Li, P., Xi, S., Guo, W., Shen, Y., ... & Wu, Y. (2022). 6G-enabled edge AI for Metaverse: Challenges, methods, and future research directions. Journal of Communications and Information Networks, 7(2), 107-121.
[16] A. Abdelhafeez, A. Aziz, and N. Khalil, “Building a Sustainable Social Feedback Loop: A Machine Intelligence Approach for Twitter Opinion Mining”, SMIJ, vol. 1, Oct. 2022.
[17] Fadi, O., Karim, Z., & Mohammed, B. (2022). A survey on Blockchain and Artificial intelligence technologies for enhancing security and privacy in smart environments. IEEE Access, 10, 93168-93186.
[18] Abdel-Basset, M., Moustafa, N., Hawash, H., & Ding, W. (2022). Deep Learning Techniques for IoT Security and Privacy (Vol. 997). New York, NY, USA: Springer.
[19] Elghaish, F., Hosseini, M. R., Matarneh, S., Talebi, S., Wu, S., Martek, I., ... & Ghodrati, N. (2021). Blockchain and the ‘Internet of Things' for the construction industry: research trends and opportunities. Automation in construction, 132, 103942.
[20] Chen, X., Tang, X., & Xu, X. (2023). Digital technology-driven smart society governance mechanism and practice exploration. Frontiers of Engineering Management, 10(2), 319-338.
[21] Sadri, H., Yitmen, I., Tagliabue, L. C., Westphal, F., Tezel, A., Taheri, A., & Sibenik, G. (2023). Integration of Blockchain and Digital Twins in the Smart Built Environment Adopting Disruptive Technologies—A Systematic Review. Sustainability, 15(4), 3713.
[22] Yang, Q., Zhao, Y., Huang, H., Xiong, Z., Kang, J., & Zheng, Z. (2022). Fusing blockchain and AI with metaverse: A survey. IEEE Open Journal of the Computer Society, 3, 122-136.
[23] Mozumder, M. A. I., Armand, T. P. T., Imtiyaj Uddin, S. M., Athar, A., Sumon, R. I., Hussain, A., & Kim, H. C. (2023). Metaverse for Digital Anti-Aging Healthcare: An Overview of Potential Use Cases Based on Artificial Intelligence, Blockchain, IoT Technologies, Its Challenges, and Future Directions. Applied Sciences, 13(8), 5127.
[24] Rejeb, A., Rejeb, K., Abdollahi, A., Al-Turjman, F., & Treiblmaier, H. (2022). The Interplay between the Internet of Things and agriculture: A bibliometric analysis and research agenda. Internet of Things, 100580.
[25] Nguyen, D. C., Ding, M., Pathirana, P. N., Seneviratne, A., Li, J., Niyato, D., ... & Poor, H. V. (2021). 6G Internet of Things: A comprehensive survey. IEEE Internet of Things Journal, 9(1), 359-383.
[26] Abdel-Basset, M., Moustafa, N., Hawash, H., Ding, W., Abdel-Basset, M., Moustafa, N., ... & Ding, W. (2022). Challenges, opportunities, and future prospects. Deep Learning Techniques for IoT Security and Privacy, 229-257.
[27] Farahani, B., Firouzi, F., & Luecking, M. (2021). The convergence of IoT and distributed ledger technologies (DLT): Opportunities, challenges, and solutions. Journal of Network and Computer Applications, 177, 102936.
[28] Saraswat, D., Bhattacharya, P., Verma, A., Prasad, V. K., Tanwar, S., Sharma, G., ... & Sharma, R. (2022). Explainable AI for healthcare 5.0: opportunities and challenges. IEEE Access.
[29] Ahmed, S. F., Alam, M. S. B., Hoque, M., Lameesa, A., Afrin, S., Farah, T., ... & Muyeen, S. M. (2023). Industrial Internet of Things enabled technologies, challenges, and future directions. Computers and Electrical Engineering, 110, 108847.
[30] Albahri, A. S., Duhaim, A. M., Fadhel, M. A., Alnoor, A., Baqer, N. S., Alzubaidi, L., ... & Deveci, M. (2023). A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion. Information Fusion.