Context Modeling and Urban Internet of Things Sensing Tools, Spatio-Temporal Fusion and Deep Learning Image Segmentation Algorithms, and Metaverse and Digital Twin Technologies in Immersive 3D and Robotic Simulation Environments
Context Modeling and Urban Internet of Things Sensing Tools, Spatio-Temporal Fusion and Deep Learning Image Segmentation Algorithms, and Metaverse and Digital Twin Technologies in Immersive 3D and Robotic Simulation Environments

Summary/Abstract: In this research, prior findings were cumulated indicating that spatial and edge computing technologies, artificial intelligence-based decision support and bio-inspired swarm robotic systems, 5G communication network and machinelearning-based wireless system operations, and multiphysics simulation and urban analytics tools assist multimedia immersive environments. A quantitative literature review of ProQuest, Scopus, and the Web of Science was carried out throughout June 2024, with search terms including “immersive 3D and robotic simulation environments” + “context modeling and urban Internet of Things sensing tools,” “spatio-temporal fusion and deep learning image segmentation algorithms,” and “metaverse and digital twin technologies.” As research published in 2022 and 2023 was inspected, only 167 articles satisfied the eligibility criteria, and 31 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, Colandr, PICO Portal, ROBIS, SluRp, and Systematic Review Accelerator.

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