HomeInternational Journal of Academic and Practical Researchvol. 3 no. 1 (2024)

Transformative Impact of Artificial Intelligence on IoT Applications: A Systematic Reviewof Advancements, Challenges, and Future Trends

Zakirullah Ezam | Amanullah Totakhail | Hamayoon Ghafory | Musawer Hakimi

Discipline: Artificial Intelligence

 

Abstract:

The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) has significantly transformed various industries, presenting both challenges and opportunities. This study conducts a comprehensive literature analysis to examine the impact of AI on enhancing IoT applications. It addresses important questions including the advancements, difficulties, opportunities, and future trends related to AI in this context. A systematic approach, following the guidelines of PRISMA, was employed to identify, select, and examine relevant academic articles published between 2016 and 2024. By carefully collecting and combining data from selected research, comprehensive insights into the current status of AI-integrated IoT applications were gained. The aim of this study is to provide a comprehensive understanding of how AI is revolutionizing IoT applications. It explores significant advancements, challenges, opportunities, and future directions. Through the utilization of a methodical approach, relevant data were collected and combined to facilitate a comprehensive examination of AI-driven advancements in different sectors. The results reveal a situation full of potential for transformation, showcasing advancements in AI in areas such as manufacturing, healthcare, home automation, urban planning, and cybersecurity. These developments emphasize the vital role of AI in enhancing operational efficiency, improving healthcare delivery, setting higher standards for residential life, and fostering sustainable urban expansion. However, it is important to address concerns around data privacy and security, the interoperability of different systems, limitations in scalability, and the lack of skilled workers in order to fully take advantage of the prospects provided by AI-powered IoT applications. Overall, the combination of AI and IoT holds significant potential for driving technological advancement and fostering interconnected and sustainable solutions in several domains. By addressing obstacles and leveraging advantages, organizations can harness the vast potential of AI-integrated IoT applications, propelling the era of digital advancement and societal development.



References:

  1. Abdullahi, M., Baashar, Y., Alhussian, H., Alwadain, A., Aziz, N., Capretz, L. F., & Abdulkadir, S. J. (2022). Detecting cybersecurity attacks in Internet of Things using artificial intelligence methods: A systematic literature review. Electronics, 11(2), 198.
  2. Al-Turjman, F. (Ed.). (2019). Artificial intelligence in IoT (1st ed.). Springer.
  3. Al-Turjman, F., Nayyar, A., Devi, A., & Shukla, P. K. (Eds.). (2021). Intelligence of things: AI-IoT based critical applications and innovations. Springer.
  4. Asghari, P., Rahmani, A. M., & Javadi, H. H. S. (2019). Internet of Things applications: A systematic review. Computer Networks, 148, 241-261.
  5. Chen, H., Khan, S., Kou, B., Nazir, S., Liu, W., & Hussain, A. (2020). A smart machine learning model for the detection of brain hemorrhage diagnosis based Internet of Things in smart cities. Complexity, 2020, 1-10.
  6. Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., & Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
  7. Fazil, A. W., Hakimi, M., Akbari, R., Quchi, M. M., & Khaliqyar, K. Q. (2023). Comparative analysis of machine learning models for data classification: An in-depth exploration. Journal of Computer Science and Technology Studies, 5(4), 160-168.
  8. Haddaway, N. R., Page, M. J., Pritchard, C. C., & McGuinness, L. A. (2022). PRISMA2020: An R package and Shiny app for producing PRISMA 2020-compliant flow diagrams, with interactivity for optimised digital transparency and open synthesis. Campbell Systematic Reviews, 18, e1230.
  9. Hansen, E. B., & Bøgh, S. (2021). Artificial intelligence and Internet of Things in small and medium-sized enterprises: A survey. Journal of Manufacturing Systems, 58, 362-372.
  10. Hassan, M. K., El Desouky, A. I., Elghamrawy, S. M., & Sarhan, A. M. (2018). Intelligent hybrid remote patient-monitoring model with cloud-based framework for knowledge discovery. Computers & Electrical Engineering, 70, 1034-1048.
  11. Hasas, A., Hakimi, M., Shahidzay, A. K., & Fazil, A. W. (2024). AI for social good: Leveraging artificial intelligence for community development. Journal of Community Service and Society Empowerment, 2(02), 196-210.
  12. Hasas, A., Zarinkhail, M. S., Hakimi, M., & Quchi, M. M. (2024). Strengthening digital security: Dynamic attack detection with LSTM, KNN, and random forest. Journal of Computer Science and Technology Studies, 6(1), 49-57.
  13. Jan, Z., Ahamed, F., Mayer, W., Patel, N., Grossmann, G., Stumptner, M., & Kuusk, A. (2023). Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities. Expert Systems with Applications, 216, 119456.
  14. Liao, B., Ali, Y., Nazir, S., He, L., & Khan, H. U. (2020). Security analysis of IoT devices by using mobile computing: A systematic literature review. IEEE Access, 8, 120331-120350.
  15. Lin, Y.-W., Lin, Y.-B., & Liu, C.-Y. (2019). AItalk: A tutorial to implement AI as IoT devices. IET Networks, 8(3), 195-202.
  16. Lv, Z., Qiao, L., Singh, A. K., & Wang, Q. (2021). AI-empowered IoT security for smart cities. ACM Transactions on Internet Technology, 21(4), 1-21.
  17. Marikyan, D., Papagiannidis, S., & Alamanos, E. (2019). A systematic review of the smart home literature: A user perspective. Technological Forecasting and Social Change, 138, 139-154.
  18. Qinxia, H., Nazir, S., Li, M., Ullah, H., Lianlian, W., & Ahmad, S. (2021). AI-enabled sensing and decision-making for IoT systems. Complexity, 2021, 1-9.
  19. Sepasgozar, S., Karimi, R., Farahzadi, L., Moezzi, F., Shirowzhan, S., Ebrahimzadeh, S. M., & Aye, L. (2020). A systematic content review of artificial intelligence and the internet of things applications in smart home. Applied Sciences, 10(9), 3074.
  20. Sepasgozar, S. M., Hawken, S., Sargolzaei, S., & Foroozanfa, M. (2019). Implementing citizen centric technology in developing smart cities: A model for predicting the acceptance of urban technologies. Technological Forecasting and Social Change, 142, 105-116.
  21. Serrano, M., Dang, H. N., & Nguyen, H. M. Q. (2018, October). Recent advances on artificial intelligence and Internet of Things convergence for human-centric applications: Internet of Things science. In Proceedings of the 8th International Conference on the Internet of Things (pp. 1-5).
  22. Singla, S. (2020). AI and IoT in healthcare. In P. Raj, J. Chatterjee, A. Kumar, & B. Balamurugan (Eds.), Internet of things use cases for the healthcare industry (pp. 1-13). Springer.
  23. Stojkoska, B. L. R., & Trivodaliev, K. V. (2017). A review of Internet of Things for smart home: Challenges and solutions. Journal of Cleaner Production, 140, 1454-1464.
  24. Wu, H., Han, H., Wang, X., & Sun, S. (2020). Research on artificial intelligence enhancing Internet of Things security: A survey. IEEE Access, 8, 153826-153848.
  25. Zhang, T., Zhao, Y., Jia, W., & Chen, M. Y. (2021). Collaborative algorithms that combine AI with IoT towards monitoring and control system. Future Generation Computer Systems, 125, 677-686.
  26. Zhou, Z., Tsang, K. F., Zhao, Z., & Wu, H. (2016). Data intelligence on the Internet of Things. Personal and Ubiquitous Computing, 20, 277-281.