ABSTRACT. In this article, previous research findings were cumulated, indicating that digital twin artificial intelligence sensing and imaging technologies, interoperable virtual and 6G wireless sensor networks, and semantic network representations shape augmented reality environments. Throughout July 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “industrial metaverse” + “mobile robotic manufacturing and automatic process control systems,” “digital twin artificial intelligence sensing and imaging technologies,” and “interoperable virtual and 6G wireless sensor networks.”As research published in 2022 and 2023 was inspected, only 167 articles satisfied the eligibility criteria, and 20 mainly empirical sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: Colandr, R package and Shiny app citationchaser, JBI SUMARI, MMAT, PICO Portal, and SWIFT-Active Screener.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: mobile robotic manufacturing; automatic process control; digital twin artificial intelligence; sensing and imaging technologies; 6G wireless sensor network; industrial metaverse

How to cite: Chaanine, L., Petrescu, I.-E., Hurjui, M. C., and Şanta, A.-M. I. (2023). “Mobile Robotic Manufacturing and Automatic Process Control Systems, Digital Twin Artificial Intelligence Sensing and Imaging Technologies, and Interoperable Virtual and 6G Wireless Sensor Networks in the Industrial Metaverse,” Journal of Self-Governance and Management Economics 11(4): 44–58. doi: 10.22381/jsme11420233.

Received 8 August 2023 • Received in revised form 23 December 2023
Accepted 26 December 2023 • Available online 30 December 2023