Object Recognition and Virtual Retail Algorithms, Metaverse and Immersive Technologies, and Simulation Modeling and Spatial Data Acquisition Tools in Extended Reality Environments
Object Recognition and Virtual Retail Algorithms, Metaverse and Immersive Technologies, and Simulation Modeling and Spatial Data Acquisition Tools in Extended Reality Environments

Summary/Abstract: The objective of this paper is to systematically review predictive maintenance and spatial data acquisition tools, metaverse technologies, and vision and navigation systems. The findings and analyses highlight that metaverse live shopping develops on behavior analysis and prediction tools, data stream clustering algorithms, and mobile geofencing technology in virtual mall environments. Through- out July 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “metaverse” + “object recognition and virtual retail algorithms,” “immersive technologies,” and “simulation modeling and spatial data acquisition tools.” As research published between 2021 and 2022 was inspected, only 139 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, I selected 27 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.

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