Human-Computer Interaction and Human-Building Interaction
Exploring AI-Integrated VR Systems: A Methodological Approach to Inclusive Digital Urban Design
Abstract
The integration of artificial intelligence (AI) and virtual reality (VR) is reshaping urban design by offering advanced tools that foster experiential engagement, real-time collaboration, and inclusive design strategies. This study explores AI-enhanced VR platforms through the development and implementation of a digital model of Loughborough University across five environments: Twinmotion, Unreal Engine, Hubs, FrameVR, and ShapesXR. As a methodological and technical evaluation, the research assesses each platform based on four core dimensions: compatibility, design and VR features, collaboration and accessibility, and AI capabilities. The results highlight the comparative strengths and limitations of each system, providing insights into their suitability for various urban design contexts. By establishing a structured evaluation framework, this study contributes to the discourse on digital urbanism and offers practical guidance for selecting and optimizing VR tools in architectural workflows. It concludes by underscoring the potential of AI–VR integration in bridging digital and physical environments within future Metaverse applications.
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Cite this paper
@Article{759aad2b,
AUTHOR = {Ehab, Ahmed and Aladawi, Ahmad and Burnett, Gary},
TITLE = {Exploring AI-Integrated VR Systems: A Methodological Approach to Inclusive Digital Urban Design},
JOURNAL = {Urban Science},
VOLUME = {9},
YEAR = {2025},
NUMBER = {6},
ARTICLE-NUMBER = {196},
URL = {https://www.mdpi.com/2413-8851/9/6/196},
ISSN = {2413-8851},
ABSTRACT = {The integration of artificial intelligence (AI) and virtual reality (VR) is reshaping urban design by offering advanced tools that foster experiential engagement, real-time collaboration, and inclusive design strategies. This study explores AI-enhanced VR platforms through the development and implementation of a digital model of Loughborough University across five environments: Twinmotion, Unreal Engine, Hubs, FrameVR, and ShapesXR. As a methodological and technical evaluation, the research assesses each platform based on four core dimensions: compatibility, design and VR features, collaboration and accessibility, and AI capabilities. The results highlight the comparative strengths and limitations of each system, providing insights into their suitability for various urban design contexts. By establishing a structured evaluation framework, this study contributes to the discourse on digital urbanism and offers practical guidance for selecting and optimizing VR tools in architectural workflows. It concludes by underscoring the potential of AI–VR integration in bridging digital and physical environments within future Metaverse applications.},
DOI = {10.3390/urbansci9060196}
}