AI Enhanced Data Processing in Cloud-Driven IoT Systems

Authors

  • Ridwan Boya Marqas * Department of Computer Science, College of Science, Knowledge University, Erbil, Iraq. https://orcid.org/0000-0002-1071-3771
  • Shaikh Saquib Jamal School of Computer Science Engineering, KIIT University, Bhubaneswar, India.
  • Ankur Singh School of Computer Science Engineering, KIIT University, Bhubaneswar, India.

https://doi.org/10.48313/siot.v3i2.89

Abstract

The convergence of Artificial Intelligence (AI), cloud computing, and Internet of Things (IoT) systems has led to significant advancements in how large-scale data is processed, managed, and utilized. AI provides advanced analytic capabilities, including machine learning (ML), predictive analytic, and real- time decision-making, which are critical for handling the massive datasets generated by IoT devices. Cloud computing platforms offer scalable infrastructure that integrates seamlessly with AI technologies, enabling enhanced IoT data processing. This paper explores how AI improves cloud-driven IoT systems, addressing key challenges such as scalability, data privacy, and energy efficiency. The study delves into the architecture of AI-enhanced cloud platforms, examines AI algorithms used in IoT data processing, and highlights the security challenges associated with integrating AI in cloud-driven IoT systems. Emerging trends such as federated learning, AIoT, and the impact of 5G networks on AI-enhanced IoT systems are also discussed. The paper concludes by identifying future research directions and practical implications for industries seeking to adopt AI-driven IoT solutions.

Keywords:

Artificial intelligence, Internet of things, Cloud computing, Data processing, Machine learning, AIoT, Federated learning, 5G

References

  1. [1] Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660. https://doi.org/10.1016/j.future.2013.01.010
  2. [2] Ahmed, E., Yaqoob, I., Hashem, I. A. T., Khan, I., Ahmed, A. I. A., Imran, M., & Vasilakos, A. V. (2017). The role of big data analytics in Internet of Things. Computer Networks, 129, 459–471. https://doi.org/10.1016/j.comnet.2017.06.013
  3. [3] Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge computing: Vision and challenges. IEEE internet of things journal, 3(5), 637–646. https://doi.org/10.1109/JIOT.2016.2579198
  4. [4] Vaquero, L. M., & Rodero-Merino, L. (2014). Finding your way in the fog: Towards a comprehensive definition of fog computing. ACM Sigcomm Computer Communication Review, 44(5), 27–32. https://doi.org/10.1145/2677046.2677052
  5. [5] Hassani, H., Silva, E. S., Unger, S., TajMazinani, M., & Mac Feely, S. (2020). Artificial intelligence (AI) or intelligence augmentation (IA): what is the future? Ai, 1(2), 8. https://doi.org/10.3390/ai1020008
  6. [6] Fakheri, S. (2022). A comprehensive review of big data applications. Big Data and Computing Visions, 2(1), 9–17. https://doi.org/10.22105/bdcv.2022.325256.1041
  7. [7] Mohammadi, M., Al-Fuqaha, A., Sorour, S., & Guizani, M. (2018). Deep learning for IoT big data and streaming analytics: A survey. IEEE Communications Surveys & Tutorials, 20(4), 2923–2960. https://doi.org/10.1109/COMST.2018.2844341
  8. [8] Bonawitz, K., Eichner, H., Grieskamp, W., Huba, D., Ingerman, A., & Ivanov, V. (2019). Towards federated learning at scale: System design. Proceedings of machine learning and systems, 1, 374–388. https://proceedings.mlsys.org/paper_files/paper/2019/file/7b770da633baf74895be22a8807f1a8f-Paper.pdf
  9. [9] Neves, F., Souza, R., Sousa, J., Bonfim, M., & Garcia, V. (2023). Data privacy in the Internet of Things based on anonymization: A review. Journal of Computer Security, 31(3), 261–291. https://doi.org/10.3233/JCS-210089
  10. [10] Giordano, G., Palomba, F., & Ferrucci, F. (2022). On the use of artificial intelligence to deal with privacy in IoT systems: A systematic literature review. Journal of Systems and Software, 193, 111475. https://doi.org/10.1016/j.jss.2022.111475

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Published

2026-06-15

Issue

Vol. 3 No. 2 (2026): Smart Internet of Things

Section

Articles

How to Cite

Marqas, R. B. ., Jamal, S. S. ., & Singh, A. . (2026). AI Enhanced Data Processing in Cloud-Driven IoT Systems. Smart Internet of Things, 3(2), 83-91. https://doi.org/10.48313/siot.v3i2.89

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