Extended Reality and Cognitive Digital Twin Technologies, 3D Space Mapping and Image Processing Computational Algorithms, and Predictive Geospatial Modeling and Simulation Tools in the Industrial Metaverse.

• Author: Henley, Susan

1. Introduction

   Metaverse engagement and experiences can be achieved through digital contact tracing and semantic communication technologies, digital twin modeling and automated speech recognition tools, and multi-sensory stimulation and machine vision algorithms. The purpose of my systematic review is to examine the recently published literature on the industrial metaverse and integrate the insights it configures on extended reality and cognitive digital twin technologies, 3D space mapping and image processing computational algorithms, and predictive geospatial modeling and simulation tools. By analyzing the most recent (2022-2023) and significant (Web of Science, Scopus, and ProQuest) sources, my paper has attempted to prove that immersive virtual experiences can be achieved by use of synthetic biometric data, predictive modeling and socio-spatial analytics tools, and multi-sensor fusion and perception systems. The actuality and novelty of this study are articulated by addressing digital twin simulation and edge computing technologies, spatial computing and virtual reality devices (Kliestik et al., 2022), and metaverse economic and industrial automation systems, that is an emerging topic involving much interest. My research problem is whether the virtual environment of the metaverse necessitates immersive and interactive technologies (Zvarikova et al., 2023), computer vision and remote sensing algorithms (Grupac and Lazaroiu, 2022), and synthetic data and simulation modeling tools.

   In this review, prior findings have been cumulated indicating that cloud computing machines, digital twin simulation and synthetic data tools, and motion control and objection recognition algorithms (Valaskova et al., 2022) are pivotal in a synthetic reality space. The identified gaps advance 3D immersive virtual reality and Web3 technologies, wearable augmented and spatial computing devices, and multiple graphic processing units. My main objective is to indicate that deep reinforcement learning and decision-making process automation tools, cognitive enhancement and immersive technologies, and spatio-temporal fusion and simulation modeling algorithms (Machova et al., 2022) optimize extended reality environments.

2. Theoretical Overview of the Main Concepts

   Deep learning-based digital image generators, 4D body scanning and virtual immersive technologies, and Internet of Things-connected machines further decentralized 3D digital worlds. Virtual twin modeling and deep learning artificial intelligence tools, digital contact tracing and remote sensing technologies, and spatial computing and environment mapping algorithms shape 3D digital environments in a fully connected metaverse. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), real-time data tracking and autonomous visual object detection tools, neural network-based recognition and resource allocation algorithms, and 3D immersive virtual reality and Web3 technologies in the industrial metaverse (section 4), spatio-temporal fusion and visual perception algorithms, sensory data mining and 3D digital twin techniques, and deep reinforcement learning and decision-making process automation tools in the industrial metaverse (section 5), extended cognitive and distributed autonomous control systems, synthetic data and simulation modeling tools, and virtual machine and spatio-temporal fusion algorithms 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

   I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout January 2023, with search terms including "the industrial metaverse" + "extended reality and cognitive digital twin technologies," "3D space mapping and image processing computational algorithms," and "predictive geospatial modeling and simulation tools." As I analyzed research published in 2022 and 2023, only 144 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, I decided on 25, chiefly 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: AMSTAR, Distiller SR, ROBIS, and SRDR (Figures 1-6).

   Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines were used that ensure the literature review is comprehensive, transparent, and replicable. The flow diagram, produced by employing a Shiny app, presents the stream of evidence-based collected and processed data through the various steps of a systematic review, designing the amount of identified, included, and removed records, and the justifications for exclusions.

4. Real-Time Data Tracking and Autonomous Visual Object Detection Tools, Neural Network-based Recognition and Resource Allocation Algorithms, and 3D Immersive Virtual Reality and Web3 Technologies in the Industrial Metaverse

   Web3-powered metaverse worlds and the industrial metaverse (Cao et al., 2023; Durana et al., 2022; Wang et al., 2022) necessitate mobile sensors and actuators, emotion detection and recognition technologies, and real-time data tracking and autonomous visual object detection tools. Virtual twin modeling and deep learning artificial intelligence tools, digital contact tracing and remote sensing technologies, and spatial computing and environment mapping algorithms shape 3D digital environments in a fully connected metaverse.

   Neural network-based recognition and resource allocation algorithms, simulation and modeling technologies, and visual digital twins (Chowdhury, 2023; Magalhaes et al., 2022; Navarro and Pita, 2023) are pivotal in the industrial metaverse. Immersive virtual experiences can be achieved by use of synthetic biometric data, predictive modeling and socio-spatial analytics tools, and multi-sensor fusion and perception systems. The...