ABSTRACT. This article reviews and advances existing literature concerning industrial digital twin and immersive holographic imaging technologies, synthetic data and geospatial analytics tools, and digital twin manufacturing and explainable artificial intelligence-based decision support systems. Throughout May 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “digital twin connected factories in the industrial metaverse” + “geospatial mapping and immersive holographic imaging technologies,” “mobile edge computing and virtual plant floor networks,” and “computer vision artificial intelligence and robotic perceptual systems.” As research published in 2022 and 2023 was inspected, only 169 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: CASP, Colandr, R package and Shiny app citationchaser, PICO Portal, ROBIS, and SRDR+.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: virtual plant floor networks; computer vision artificial intelligence; robotic perceptual systems; digital twin; connected factories; industrial metaverse

How to cite: Popescu, G. H., Iacob, S. E., Poliakova, A., and Dumitrescu, C.-O. (2023). “Geospatial Mapping and Immersive Holographic Imaging Technologies, Mobile Edge Computing and Virtual Plant Floor Networks, and Computer Vision Artificial Intelligence and Robotic Perceptual Systems for Digital Twin Connected Factories in the Industrial Metaverse,” Economics, Management, and Financial Markets 18(4): 39–53. doi: 10.22381/emfm18420233.

Received 16 June 2023 • Received in revised form 20 December 2023
Accepted 26 December 2023 • Available online 30 December 2023