ABSTRACT. This paper draws on a substantial body of theoretical and empirical research on wireless visual sensor networks, 3D image modeling and tools, and industrial extended reality technologies. A quantitative literature review of ProQuest, Scopus, and the Web of Science was carried out throughout May 2024, with search terms including “virtual manufacturing machines in immersive industrial metaverse” + “3D computer vision-based production and multi-sensory extended reality technologies,” “robotic perceptual and cyber-physical production systems,” and “artificial intelligence-powered prediction and virtual twin modeling tools.” As research published in 2022 and 2023 was inspected, only 166 articles satisfied the eligibility criteria, and 18 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: CASP, Catchii, JBI SUMARI, PICO Portal, SluRp, and SWIFT-Active Screener.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: 3D computer vision; production; multi-sensory extended reality; artificial intelligence; virtual manufacturing machine; immersive industrial metaverse

How to cite: Poliak, M., Curteanu, A.-B., Pantovic, D., Condeianu, O., and Samoilă, A. (2024). “3D Computer Vision-based Production and Multi-Sensory Extended Reality Technologies, Robotic Perceptual and Cyber-Physical Production Systems, and Artificial Intelligence-powered Prediction and Virtual Twin Modeling Tools for Virtual Manufacturing Machines in Immersive Industrial Metaverse,” Journal of Self-Governance and Management Economics 12(3): 54–68. doi: 10.22381/jsme12320244.

Received 17 June 2024 • Received in revised form 18 September 2024
Accepted 22 September 2024 • Available online 28 September 2024