Virtual Reality-based Visual Perception and Multi-Sensory Tracking Technologies, Geospatial Mapping and Simulation Modeling Tools, and Image Recognition and Cognitive Artificial Intelligence Algorithms in the Industrial Metaverse.

Date01 December 2022
AuthorGajdosikova, Dominika
  1. Introduction

    Mobile location data, monitoring and sensing technologies, and deep reinforcement learning and virtual navigation tools further 3D immersive content in extended reality environments. The purpose of our systematic review is to examine the recently published literature on the industrial metaverse and integrate the insights it configures on virtual reality-based visual perception and multi-sensory tracking technologies, geospatial mapping and simulation modeling tools, and image recognition and cognitive artificial intelligence algorithms. By analyzing the most recent (2022) and significant (Web of Science, Scopus, and ProQuest) sources, our paper has attempted to prove that sensing and computing technologies, biometrics data fusion, and artificial intelligence-powered search capabilities enable the virtual economy of the metaverse and digital hyper-realistic worlds. The actuality and novelty of this study are articulated by addressing digital twin simulations of machine networks across collaborative 3D design environments and the industrial metaverse, that is an emerging topic involving much interest. Our research problem is whether immersive virtual environments and blockchain-based virtual worlds integrate geospatial mapping and simulation modeling tools (Kliestik et al, 2022), dynamic routing and cognitive modeling technologies, and mobile location and geospatial big data analytics.

    In this review, prior findings have been cumulated indicating that computational intelligence and context awareness tools, metaverse assets and services, and socio-spatial analytics and immersive decentralized networking tools are pivotal in the blockchain-based virtual economy. The identified gaps advance digital twin and geospatial mapping technologies (Zvarikova et al, 2023), cognitive and behavioral algorithms, and machine learning-based image recognition and intelligent data processing tools. Our main objective is to indicate that voice recognition software, real-time predictive and mobile location analytics, and ambient intelligence and virtual navigation tools (Grupac and Lazaroiu, 2022) articulate augmented reality-powered immersive spaces. This systematic review contributes to the literature on motion capture, augmented reality, and edge computing technologies, big data processing tools (Valaskova et al, 2022), and multi-sensory stimulation algorithms by clarifying that the virtual environment of the metaverse integrates simulation and modeling technologies (Machova et al., 2022), neural network-based recognition and remote sensing algorithms, and explainable artificial intelligence-based decision support systems.

  2. Theoretical Overview of the Main Concepts

    Immersive metaverse experiences can be attained through user identification and data fusion technologies, Internet of Things sensing infrastructures, and synthetic data and image recognition tools in extended reality environments.

    The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), context recognition and simulation modeling tools, dynamic routing and immersive 3D technologies, and path planning and computer vision algorithms in the industrial metaverse (section 4), 3D generative modeling and contextual data monitoring tools, spatial computing and machine learning-based object recognition technologies, and bio-sensing and autonomous cognitive systems in the industrial metaverse (section 5), cognitive decision-making and deep learning algorithms, virtual reality-based visual perception and multi-sensory tracking technologies, and machine learning-based image recognition and intelligent data processing tools in the industrial metaverse (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10).

  3. Methodology

    Throughout July 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including "the industrial metaverse" + "virtual reality-based visual perception and multi-sensory tracking technologies," "geospatial mapping and simulation modeling tools," and "image recognition and cognitive artificial intelligence algorithms." As we inspected research published in 2022, only 152 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 18, generally empirical, sources (Tables 1 and 2). Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, ROBIS, and SRDR (Figures 1-6).

  4. Context Recognition and Simulation Modeling Tools, Dynamic Routing and Immersive 3D Technologies, and Path Planning and Computer Vision Algorithms in the Industrial Metaverse

    Immersive 3D virtual environments and the industrial metaverse (Ganchev et al., 2023; Park et al., 2023; Wan et al., 2022; Yao et al., 2022) necessitate context recognition and simulation modeling tools, cognitive enhancement and automation technologies, and biometric authentication and bio-sensing systems. Mobile location data, monitoring and sensing technologies, and deep reinforcement learning and virtual navigation tools further 3D immersive content in extended reality environments.

    The industrial metaverse and immersive decentralized 3D digital worlds (Han et al., 2023; Khalaj et al., 2023; Lee and Kundu, 2022; Wang et al., 2022) require geospatial mapping and immersive decentralized networking tools, cognitive and behavioral algorithms, and cloud computing and digital contact tracing technologies. Sensing and computing technologies, biometrics data fusion, and artificial intelligence-powered search capabilities enable the virtual economy of the metaverse and digital hyper-realistic worlds.

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