ABSTRACT. The purpose of this study is to examine real-time object detection, Internet of Things sensors, preventive and predictive maintenance, and 3D simulation tools in the industrial metaverse. Throughout July 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “photo-realistic simulation environments and the interconnected metaverse” + “digital twin-enabled industrial Internet of Things,” “computer vision and spatio-temporal fusion algorithms,” and “tactile sensing and behavior modeling technologies.” As we inspected research published in 2022, only 149 articles satisfied the eligibility criteria. By removing controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 16, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, MMAT, and SRDR.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: digital twin; industrial Internet of Things; computer vision; spatio-temporal fusion algorithms; tactile sensing and behavior modeling technologies; photo-realistic simulation environments; interconnected metaverse

How to cite: Gajdosikova, D., Bilan, S., Tucmeanu, A. I., and Văduva, C. (2022). “Digital Twin-enabled Industrial Internet of Things, Computer Vision and Spatio-Temporal Fusion Algorithms, and Tactile Sensing and Behavior Modeling Technologies in Photo-Realistic Simulation Environments and across the Interconnected Metaverse,” Journal of Self-Governance and Management Economics 10(4): 67–81. doi: 10.22381/jsme10420225.

Received 17 August 2022 • Received in revised form 24 December 2022
Accepted 27 December 2022 • Available online 30 December 2022