Multi-Modal Synthetic Data Fusion and Analysis, Virtual Immersive and Cognitive Neuro-Engineering Technologies, and Bio-inspired Computational Intelligence and Deep Learning Algorithms in the Industrial Metaverse
Multi-Modal Synthetic Data Fusion and Analysis, Virtual Immersive and Cognitive Neuro-Engineering Technologies, and Bio-inspired Computational Intelligence and Deep Learning Algorithms in the Industrial Metaverse

Summary/Abstract: The aim of this systematic review is to synthesize and analyze immersive and interactive technologies, asset maintenance simulations, and real-time data-based digital twins in the industrial metaverse. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout August 2022, with search terms including “the industrial metaverse” + “multi-modal synthetic data fusion and analysis,” “virtual immersive and cognitive neuro-engineering technologies,” and “bio-inspired computational intelligence and deep learning algorithms.” As we analyzed research published in 2022, only 151 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 20, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR.

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