Aplicación de herramientas de Inteligencia Artificial en el manejo del lenguaje de patrones para Proyectos Urbanos

Abstract

This research analyzes the integration of artificial intelligence tools with BIM Revit software to automate the recommendation and adaptation of Christopher Alexander's Pattern Language in urban projects. It focuses on enhancing the quality and sustainability of urban design by addressing the lack of advanced tools that facilitate the implementation of patterns in current urban environments, offering customized and efficient solutions. The development was structured into four main phases: analysis, modeling, integration, and evaluation. Relevant patterns were selected in the analysis phase, with a focus on Pattern 16, which addresses public transportation networks. An urban environment was modeled in Revit, featuring a central plaza as a transit hub to maximize accessibility. During the integration phase, tools such as GPT models, LookX.ai, and Autodesk Forma were employed to analyze and optimize the design. Finally, the solutions were evaluated in terms of coherence, applicability, and sustainability. The results demonstrated the capability of the tools to create proposals aligned with Alexander’s principles, emphasizing sustainability and functionality. Environmental analyses and rendered images enhanced the visual and functional design of the urban model, although limitations were identified in interoperability and dynamic representation. Keywords: Artificial Intelligence, Pattern Language, Urban Design, BIM, Sustainability