Smart City Digital Twins, 3D Modeling and Visualization Tools, and Spatial Cognition Algorithms in Artificial Intelligence-based Urban Design and Planning
Smart City Digital Twins, 3D Modeling and Visualization Tools, and Spatial Cognition Algorithms in Artificial Intelligence-based Urban Design and Planning

Summary/Abstract: The aim of this systematic review is to synthesize and analyze smart city digital twins, 3D modeling and visualization tools, and spatial cognition algorithms in artificial intelligence-based urban design and planning. With increasing evidence of 3D virtual simulation technology, big data-driven urban analytics, and real-time decision support systems, there is an essential demand for comprehending whether Internet of Things-based digital twins require artificial intelligence-based urban design and planning and real-time urban data. In this research, prior findings were cumulated indicating that data-driven planning technologies leverage multi-sensor remote sensing data, simulation modeling algorithms, and augmented analytics tools. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout April 2022, with search terms including “artificial intelligence-based urban design and planning” + “smart city digital twins,” “3D modeling and visualization tools,” and “spatial cognition algorithms.” As I analyzed research published in 2022, only 178 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, I decided on 33, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR.

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