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AI-enabled data management for digital twin networks

Ak, Elif; Yurdakul, Gökhan; Al-Dubai, Ahmed; Canberk, Berk

Authors

Elif Ak

Gökhan Yurdakul



Contributors

Hamed Ahmadi
Editor

Trung Q. Duong
Editor

Avishek Nag
Editor

Vishal Sharma
Editor

Octavia A. Dobre
Editor

Abstract

As we have discussed in previous chapters, digital twins establish contextual relationships with the surrounding entities, providing a holistic view of interconnected systems and environments. With the growing complexity and abundance of data generated by digital twins, effective data management strategies have become paramount. This chapter delves into AI-enabled data management for digital twins, exploring how artificial intelligence techniques empower the collecting, storing, integrating, analyzing, and utilizing of diverse and voluminous data within the digital twin ecosystem. We will see how 6G and IoT networks can unlock valuable insights and optimize operational processes in many aspects by leveraging AI.

Citation

Ak, E., Yurdakul, G., Al-Dubai, A., & Canberk, B. (2024). AI-enabled data management for digital twin networks. In H. Ahmadi, T. Q. Duong, A. Nag, V. Sharma, B. Canberk, & O. A. Dobre (Eds.), . Institution of Engineering and Technology (IET). https://doi.org/10.1049/pbte109e_ch3

Online Publication Date Jun 5, 2024
Publication Date 2024
Deposit Date Oct 11, 2024
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
Pages 49-81
Series Title Digital Twins for 6G: Fundamental theory, technology and applications
ISBN 9781839537455
DOI https://doi.org/10.1049/pbte109e_ch3