Visual Analytics and Digital Twin Modeling Tools, Spatio-Temporal Fusion and Predictive Modeling Algorithms, and Deep Learning-based Sensing and Image Recognition Technologies in Data-driven Smart Sustainable Cities and Immersive Multisensory Virtual
Visual Analytics and Digital Twin Modeling Tools, Spatio-Temporal Fusion and Predictive Modeling Algorithms, and Deep Learning-based Sensing and Image Recognition Technologies in Data-driven Smart Sustainable Cities and Immersive Multisensory Virtual

Summary/Abstract: This paper draws on a substantial body of theoretical and empirical research on urban big data analytics, immersive virtual and data-driven planning technologies, and smart city logistics deployed in smart networked environments. A quantitative literature review of ProQuest, Scopus, and the Web of Science was carried out throughout April 2023, with search terms including “data-driven smart sustainable cities and immersive multisensory virtual spaces” + “visual analytics and digital twin modeling tools,” “spatio-temporal fusion and predictive modeling algorithms,” and “deep learning-based sensing and image recognition technologies.” As research published in 2022 and 2023 was inspected, only 146 articles satisfied the eligibility criteria, and 21 mainly empirical sources were selected. 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.

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