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Machine Vision Algorithms, Sensory Data Mining Techniques, and Geospatial Mapping Tools in the Blockchain-based Virtual Economy

Machine Vision Algorithms, Sensory Data Mining Techniques, and Geospatial Mapping Tools in the... The present study systematically reviews the existing research on immersive virtual reality experiences in the retail metaverse. My findings indicate that real-time sensor data and machine vision algorithms enhance customer engagement behaviors across virtual marketplaces and immersive interconnected virtual worlds. I contribute to the literature by clarifying that big data analytics, operational modeling tools, customer monitoring systems, and semantic vector search technology shape consumption patterns and buying habits in immersive virtual worlds. Throughout March 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “the blockchain-based virtual economy” + “machine vision algorithms,” “sensory data mining techniques,” and “geospatial mapping tools.” As research published between 2021 and 2022 was inspected, only 155 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 27 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR. Keywords: immersive metaverse experiences; customer behavior analytics; augmented reality shopping tools; ambient scene detection tools; visual analytics; sensory data mining techniques http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Contemporary Philosophy Addleton Academic Publishers

Machine Vision Algorithms, Sensory Data Mining Techniques, and Geospatial Mapping Tools in the Blockchain-based Virtual Economy

Adela-Claudia Cuțitoi
Review of Contemporary Philosophy , Volume 21 (1): 16 – Jan 1, 2022
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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1841-5261
eISSN
2471-089X
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Abstract

The present study systematically reviews the existing research on immersive virtual reality experiences in the retail metaverse. My findings indicate that real-time sensor data and machine vision algorithms enhance customer engagement behaviors across virtual marketplaces and immersive interconnected virtual worlds. I contribute to the literature by clarifying that big data analytics, operational modeling tools, customer monitoring systems, and semantic vector search technology shape consumption patterns and buying habits in immersive virtual worlds. Throughout March 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “the blockchain-based virtual economy” + “machine vision algorithms,” “sensory data mining techniques,” and “geospatial mapping tools.” As research published between 2021 and 2022 was inspected, only 155 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 27 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR. Keywords: immersive metaverse experiences; customer behavior analytics; augmented reality shopping tools; ambient scene detection tools; visual analytics; sensory data mining techniques

Journal

Review of Contemporary Philosophy – Addleton Academic Publishers

Published: Jan 1, 2022

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