An Artificial Intelligence-Based Framework for Automated Information Inquiry from Building Information Models Using Natural Language Processing and Ontology

Document Type

Conference Proceeding

Publication Title

Computing in Civil Engineering 2023: Visualization, Information Modeling, and Simulation - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023

Publication Date

1-1-2024

Abstract

Building information modeling (BIM), a novel technology in the architectural engineering and construction (AEC) industry, contains various data and information, which is so practical and can be required by many stakeholders during the project's life cycle. For non-technical users with limited or no skill in dealing with BIM software, access to this data can be time-consuming, and tedious. Automating the information extraction from BIM models can efficiently address this need. In this regard, this research proposes an artificial intelligence (AI)-based framework to facilitate information extraction from BIM models. Therefore, the user can ask questions and receive answers from the framework. Utilizing natural language processing (NLP), an ontology database (IfcOWL) and an NLP method [latent semantic analysis (LSA)], the purpose of the user is understood by the framework through syntactic analysis and semantic understanding of the question and answer to the user, based on functions. The results show that the speed of answering the questions in this framework is up to five times faster than the manual while maintaining high accuracy.

First Page

381

Last Page

389

DOI

10.1061/9780784485231.046

ISBN

9780784485231

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