ABSTRACT. Based on an in-depth survey of the literature, the purpose of the paper is to explore metaverse and digital twin technologies, 3D contextual data, virtual machine remote monitoring and data processing tools, and multimodal generative artificial intelligence and computational imaging systems. Throughout January 2024, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “virtual and simulated machines and factories in the industrial metaverse” + “multi-sensory extended reality and swarm robot autonomous navigation technologies,” “digital twin data modeling and visualization,” and “Internet of Things-based process and production planning.” As research published in 2022 and 2023 was inspected, only 167 articles satisfied the eligibility criteria, and 19 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: Abstrackr, CADIMA, Citationchaser, DistillerSR, JBI SUMARI, and Litstream.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: virtual and simulated machines and factories; industrial metaverse; multi-sensory extended reality; swarm robot autonomous navigation; digital twin data; Internet of Things-based process and production planning

How to cite: Pârvu, I. A., Kuzman, B., Stamule, S., Szydło, J., and Saremi, M. (2024). “Virtual and Simulated Machines and Factories in the Industrial Metaverse: Multi-Sensory Extended Reality and Swarm Robot Autonomous Navigation Technologies, Digital Twin Data Modeling and Visualization, and Internet of Things-based Process and Production Planning,” Journal of Self-Governance and Management Economics 12(2): 62–76. doi: 10.22381/jsme12220244.

Received 27 January 2024 • Received in revised form 21 June 2024
Accepted 23 June 2024 • Available online 29 June 2024