This study investigates the integration of Artificial Intelligence (AI) within the Infrastructure Building Information Modeling (I-BIM) process, applied to the design of a road and gravity-based utility network using Autodesk tools (InfraWorks, Civil 3D, and Navisworks). A custom AI Agent—implemented as a self-improving chatbot—was developed to assist users throughout the workflow The study presents an AI-enhanced infrastructure design workflow aimed at reducing design time and human error compared to traditional manual methods. A custom AI Agent—capable of autonomous reasoning and self-improvement—was integrated to support users throughout the design process. The research compares this AI-assisted approach with conventional workflows and also contrasts non-agent chatbots with more advanced AI agents. The study also highlights key methodological limitations, indicating that although the AI Agent demonstrates strong potential, further research is necessary to enhance its integration and ensure its reliability in practical infrastructure design scenarios.
Integration of Artificial Intelligence and Visual Programming Languages Within Infrastructure-Building Information Modeling Workflow: A Case Study / Intignano, M., Serra, P., Biancardo, S.A., Dell'Acqua, G.. - 1906:(2026), pp. 759-769. [10.1007/978-3-032-18771-0_69]
Integration of Artificial Intelligence and Visual Programming Languages Within Infrastructure-Building Information Modeling Workflow: A Case Study
Intignano, Mattia;Serra, Pietro;Biancardo, Salvatore Antonio
;Dell'Acqua, Gianluca
2026
Abstract
This study investigates the integration of Artificial Intelligence (AI) within the Infrastructure Building Information Modeling (I-BIM) process, applied to the design of a road and gravity-based utility network using Autodesk tools (InfraWorks, Civil 3D, and Navisworks). A custom AI Agent—implemented as a self-improving chatbot—was developed to assist users throughout the workflow The study presents an AI-enhanced infrastructure design workflow aimed at reducing design time and human error compared to traditional manual methods. A custom AI Agent—capable of autonomous reasoning and self-improvement—was integrated to support users throughout the design process. The research compares this AI-assisted approach with conventional workflows and also contrasts non-agent chatbots with more advanced AI agents. The study also highlights key methodological limitations, indicating that although the AI Agent demonstrates strong potential, further research is necessary to enhance its integration and ensure its reliability in practical infrastructure design scenarios.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


