ABSTRACT. This article reviews and advances existing literature concerning geolocation data mining and tracking, machine learning-based object recognition and digital twin technologies, and metaverse engagement metrics. I contribute to the literature by indicating that remote sensing and edge artificial intelligence computing systems, context awareness and machine learning-based image recognition tools, and wearable haptic garments enable immersive hyper-connected virtual spaces. Throughout April 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “3D cognitive digital twin metaverse” + “remote sensing and edge artificial intelligence computing systems,” “environment perception and geospatial mapping technologies,” and “simulation modeling and machine learning-based image recognition tools.” As research published in 2022 and 2023 was inspected, only 184 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 41 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR.

Keywords: remote sensing; edge artificial intelligence computing systems; environment perception; geospatial mapping technologies; simulation modeling; machine learning; image recognition tools; 3D cognitive digital twin metaverse

How to cite: Aldea, C.-I. (2023). “Remote Sensing and Edge Artificial Intelligence Computing Systems, Environment Perception and Geospatial Mapping Technologies, and Simulation Modeling and Machine Learning-based Image Recognition Tools in the 3D Cognitive Digital Twin Metaverse,” Review of Contemporary Philosophy 21: 208–225. doi: 10.22381/RCP22202312.

Received 25 May 2023 • Received in revised form 23 August 2023
Accepted 26 August 2023 • Available online 30 August 2023

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