ABSTRACT. Despite the relevance of virtual 3D scene simulation and industrial robotic systems, digital twin-enabled edge and industrial artificial Internet of Things networks, and deep learning-based ambient sound processing and cloud-based object tracking tools, only limited research has been conducted on this topic. Throughout June 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “the interactive industrial metaverse” + “context-aware augmented reality and mobile robotic manufacturing systems,” “3D computer vision-based production and machine intelligence technologies,” and “remote sensing and digital twin simulation tools.” As research published in 2022 and 2023 was inspected, only 171 articles satisfied the eligibility criteria, and 19 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: BIBOT, Eppi-Reviewer, METAGEAR package for R, SluRp, SWIFT-Active Screener, and Systematic Review Accelerator.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: context-aware augmented reality; mobile robotic manufacturing; 3D computer vision-based production; digital twin simulation; virtual factories; industrial metaverse

How to cite: Sedlarski, T., AlAkoum, A., Drugău Constantin, A.-L., and Melenciuc, M. (2023). “Context-aware Augmented Reality and Mobile Robotic Manufacturing Systems, 3D Computer Vision-based Production and Machine Intelligence Technologies, and Remote Sensing and Digital Twin Simulation Tools for Virtual Factories in the Interactive Industrial Metaverse,” Economics, Management, and Financial Markets 18(4): 54–68. doi: 10.22381/emfm18420234.

Received 13 July 2023 • Received in revised form 22 December 2023
Accepted 25 December 2023 • Available online 30 December 2023