Articles
Application of Artificial Intelligence in the Pattern Language for Urban Projects
Abstract
The integration of artificial intelligence tools with the Building Information Modeling (BIM) software Revit was approached as a support strategy for applying Christopher Alexander’s Pattern Language in urban projects. The study analyzed how generative language models (GPT), combined with visualization and environmental simulation platforms, can contribute to interpreting and reinforcing the coherence, applicability, and sustainability of urban design. The research was carried out in four phases: analysis, modeling, integration, and evaluation. In the first phase, relevant patterns were selected, with an emphasis on Pattern 16, which focused on public transportation networks. Subsequently, an urban environment was modeled in Revit, with a central plaza as a transfer node to enhance accessibility. During the integration phase, three GPT models (My Generative AI Design Assistant, Innovator Architect, and Advanced IFC Editor) were applied to generate qualitative recommendations on accessibility, sustainability, and public space organization, while the LookX.ai platform was used to obtain photorealistic renders of the model, and Autodesk Forma for environmental simulations in two contrasting urban contexts. Finally, the proposals were evaluated in terms of coherence, applicability, and sustainability. The results showed solutions aligned with Alexander’s principles, highlighting the sustainability and functionality of the design. Environmental analyses and visual representations enriched the proposal, though limitations in interoperability and in the dynamic representation of the environment were identified.
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References
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