ABSTRACT. The present study systematically reviews the existing research on immersive decentralized 3D digital worlds and the industrial metaverse. Throughout August 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “the immersive industrial metaverse” + “virtual modeling and image-based visual computing technologies,” “Internet of Things-based decision support and remote sensing systems,” and “context awareness and spatio-temporal fusion algorithms.” As research published in 2022 was inspected, only 151 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 17 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: virtual modeling; image-based visual computing technologies; Internet of Things-based decision support; remote sensing systems; context awareness and spatio-temporal fusion algorithms; immersive industrial metaverse

How to cite: Goodman, C., Geambazi, R.-Ș., and Constantinescu, M. (2022). “Virtual Modeling and Visual Computing Technologies, Internet of Things-based Decision Support and Remote Sensing Systems, and Context Awareness and Spatio-Temporal Fusion Algorithms in the Immersive Industrial Metaverse,” Economics, Management, and Financial Markets 17(4): 58–72. doi: 10.22381/emfm17420224.

Received 19 September 2022 • Received in revised form 23 December 2022
Accepted 28 December 2022 • Available online 30 December 2022