Remote Sensing Data Fusion Techniques, Multimodal Behavioral Predictive and Mobile Location Analytics, and Spatial Cognition and Context Awareness Algorithms in the Metaverse Economy

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Abstract

The purpose of this study is to examine big geospatial data and user journey analytics, metaverse assets and services, and cyber-physical cognitive and immersive visualization systems. We contribute to the literature on virtual modeling and immersive 3D technologies, context awareness and machine vision algorithms, and sensor and actuator devices by showing that immersive digital worlds require computer vision and cognitive decision-making algorithms, deep learning-based sensing and spatial computing technologies, and virtual navigation and data mining tools. Throughout December 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “the metaverse economy” + “remote sensing data fusion techniques,” “multimodal behavioral predictive and mobile location analytics,” and “spatial cognition and context awareness algorithms.” As we inspected research published between 2022 and 2023, only 179 articles satisfied the eligibility criteria. By removing controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 36, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, MMAT, and SRDR.

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Horak, J., Voumik, L. C., & Popescu, G. H. (2023). Remote Sensing Data Fusion Techniques, Multimodal Behavioral Predictive and Mobile Location Analytics, and Spatial Cognition and Context Awareness Algorithms in the Metaverse Economy. Linguistic and Philosophical Investigations, 22, 77–93. https://doi.org/10.22381/lpi2220235

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