Bridging artificial intelligence with building information modeling: development and evaluation of a conversational assistant for real-time model management

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dc.contributor.authorFernandes de Oliveira, David
dc.contributor.examiningcommitteeMehran, Babak (Civil Engineering)
dc.contributor.examiningcommitteeAsadzadeh, Masoud (Civil Engineering)
dc.contributor.supervisorGuven Isin, Gursans
dc.date.accessioned2024-03-21T19:48:17Z
dc.date.available2024-03-21T19:48:17Z
dc.date.issued2024-03-21
dc.date.submitted2024-03-21T05:02:44Zen_US
dc.date.submitted2024-03-21T18:02:49Zen_US
dc.degree.disciplineCivil Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)
dc.description.abstractThe integration of Artificial Intelligence (AI) into Building Information Modeling (BIM) has the potential to revolutionize the Architecture, Engineering, and Construction (AEC) industry by enhancing efficiency, improving decision-making processes, and making BIM models more accessible and intuitive for professionals across various disciplines. This thesis introduces DAVE (Digital Assistant for Virtual Engineering), a prototype of a Generative Pre-trained Transformer (GPT)-powered digital assistant designed to facilitate seamless, real-time interactions and updates within BIM environments through natural language processing (NLP) and voice commands. By integrating with Autodesk Revit using Python scripts, the Revit API, and the OpenAI API, DAVE demonstrates a practical application of conversational AI in the AEC sector, aiming to make BIM workflows more intuitive and reducing the cognitive load on users. The development and implementation of DAVE involve a comprehensive system architecture that combines Python scripting, a Dynamic-Link Library (DLL), and a JavaScript Object Notation (JSON) file for efficient data management and interaction with BIM models. The prototype's testing and validation phase highlights its capability to handle a variety of commands, from simple tasks such as undoing actions to more complex operations like updating room names and numbers. Through a detailed analysis of system performance and user interaction, this thesis explores the challenges and limitations of integrating AI with BIM, including scalability, data integrity, and the quality of user queries. Despite these challenges, DAVE's successful demonstration of real-time BIM model management through voice and natural language commands marks a significant step forward in the digital transformation of the AEC industry. This thesis not only contributes to the ongoing development of AI applications within BIM but also lays the groundwork for future research aimed at expanding the capabilities of AI-powered assistants in the AEC sector. By addressing the current system limitations and exploring avenues for further enhancements, such as interoperability with other BIM software and improving the efficiency of information retrieval, the study paves the way for a more connected, intelligent, and user-centric future in the built environment. The development of DAVE embodies the potential of conversational AI to revolutionize architectural and construction methodologies, offering insights into how the AEC industry can leverage AI to achieve greater efficiency, sustainability, and innovation in project management and execution.
dc.description.noteMay 2024
dc.identifier.urihttp://hdl.handle.net/1993/38070
dc.language.isoeng
dc.rightsopen accessen_US
dc.subjectBuilding Information Modeling
dc.subjectBIM
dc.subjectNatural Language Processing
dc.subjectGPT
dc.subjectVirtual Assistant
dc.subjectArtificial Intelligence
dc.subjectConversational AI
dc.titleBridging artificial intelligence with building information modeling: development and evaluation of a conversational assistant for real-time model management
dc.typemaster thesisen_US
local.subject.manitobano
oaire.awardTitleUniversity of Manitoba Graduate Fellowship
project.funder.identifierhttps://doi.org/10.13039/100010318
project.funder.nameUniversity of Manitoba
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