Industrial Digital Twins at the Nexus of NextG Wireless Networks and Computational Intelligence: A Survey
Shah Zeb, Aamir Mahmood, Syed Ali Hassan, MD. Jalil Piran, Mikael, Gidlund, Mohsen Guizani

TL;DR
This survey explores how digital twins integrate with NextG wireless networks and computational intelligence to enhance Industry 4.0 manufacturing through communication, data analytics, and networked computing.
Contribution
It systematically reviews recent research on the role of NextG wireless, edge/cloud computing, and data analytics in enabling industrial digital twins.
Findings
Highlights the importance of 5G and beyond for DT deployment.
Discusses strategies for DT integration across industrial communication layers.
Identifies future challenges and directions for industrial DT adoption.
Abstract
By amalgamating recent communication and control technologies, computing and data analytics techniques, and modular manufacturing, Industry~4.0 promotes integrating cyber-physical worlds through cyber-physical systems (CPS) and digital twin (DT) for monitoring, optimization, and prognostics of industrial processes. A DT is an emerging but conceptually different construct than CPS. Like CPS, DT relies on communication to create a highly-consistent, synchronized digital mirror image of the objects or physical processes. DT, in addition, uses built-in models on this precise image to simulate, analyze, predict, and optimize their real-time operation using feedback. DT is rapidly diffusing in the industries with recent advances in the industrial Internet of things (IIoT), edge and cloud computing, machine learning, artificial intelligence, and advanced data analytics. However, the existing…
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Taxonomy
TopicsDigital Transformation in Industry · IoT and Edge/Fog Computing · Flexible and Reconfigurable Manufacturing Systems
