NGWN - Next Generation of Wireless Networks based on Industry 5.0 in Computational Intelligence

Authors

  • Sagar Gulati Deputy Director Academics, iNurture Education Solutions, Bengaluru
  • Sumit Kumar Associate Professor, Dept. of AI & ML, COER University, Roorkee
  • Om Prakash Sharma Associate Professor, School of IT, SRM University, Sikkim
  • Rajiv Ranjan Patel Assistant Professor, Dept. of AI & ML, COER University, Roorkee
  • Vedala Naga Sailaja Associate Professor, Business School, KLEF Deemed to be University, Green Fields, Vaddeswaram, A.P – 522302

Keywords:

computational intelligence, next generation of wireless networks, Industry 5.0

Abstract

Systems that are aware of their context can automatically adjust and monitor how they operate based on the execution context in which they are introduced. Nevertheless, the goal necessitates combining the cyber-physical worlds by leveraging Industry 5.0 technology enablers. This survey-based tutorial aims to address how the next generation of wireless networks (NGWNs) and the emerging computational intelligence (CI) paradigm can come together to meet the demanding computational and communication needs of the Industry 5.0 vision's technological enablers. In this article, we look at and evaluate the most recent advancements in ideas and technologies, including software service architectures, open radio access networks, CI tools and structures, network-in-box design, and potential enabling services. These developments are essential for developing CINGWN objectives that satisfy the demands of the Industry 5.0 vision. It is recommended that future research concentrate on creating transparent, reliable, and quantifiable technologies that offer a fulfilling work environment motivated by practical requirements.

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References

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Published

27.12.2023

How to Cite

Gulati, S. ., Kumar, S. ., Sharma, O. P. ., Patel, R. R. ., & Sailaja, V. N. . (2023). NGWN - Next Generation of Wireless Networks based on Industry 5.0 in Computational Intelligence. International Journal of Intelligent Systems and Applications in Engineering, 12(9s), 119–127. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4211

Issue

Vol. 12 No. 9s (2024)

Section

Research Article

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