Machine Learning Based Industrial Engineering With 6G Technology

Authors

  • SUDHAKAR K , SENTHILKUMAR S , NOOR SUMAIYA , NIVEDITHA S , DEEMA MOHAMMED ALSEKAIT

DOI:

https://doi.org/10.47750/pnr.2022.13.S09.46

Abstract

The "Ubiquitous Wireless Intelligence" concept of 6G opens up a variety of technological innovation paths, some of which are aided by machine learning and artificial intelligence, the two topics on which this work focuses. However, this advancement in ICT comes at a time when people are more driven than ever to use digital inclusion to reduce social and economic inequality while also giving the UN Sustainable Development Goals priority (SDGs). The document is divided into four sections: what 6G offers, the gaps and technical hurdles now present, the role of machine learning in many aspects, and finally the difficulties associated with incorporating AI/ML For the first time, a brand-new theoretical framework, denoted as 6GIIoE, was developed for the 6G-enabled IIoE system. This paper presents the vision of future 6G wireless correspondence and its network design. We talk about the emerging advances such as artificial intelligence, terahertz correspondences, optical wireless innovation, free space optic organization, blockchain, three dimensional networking, quantum correspondences, automated ethereal vehicle, without cell correspondences, integration of wireless information and energy move, integration of sensing and correspondence, integration of access-backhaul networks, dynamic organization slicing, holographic beamforming, and enormous information examination that can help the 6G design improvement in guaranteeing the QoS. We present the normal applications with the prerequisites and the potential innovations for 6Gcorrespondence. We likewise outline the potential difficulties and research headings to arrive at this objective.

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Published

2022-11-09 — Updated on 2022-11-09

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How to Cite

SUDHAKAR K , SENTHILKUMAR S , NOOR SUMAIYA , NIVEDITHA S , DEEMA MOHAMMED ALSEKAIT. (2022). Machine Learning Based Industrial Engineering With 6G Technology. Journal of Pharmaceutical Negative Results, 372–385. https://doi.org/10.47750/pnr.2022.13.S09.46

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Articles