Prospects of Integrating BIM and NLP for Automatic Construction Schedule Management

Prospects of Integrating BIM and NLP for Automatic Construction Schedule Management Akarsth Kumar Singh, Aritra Pal, Pavan Kumar, Jacob J. Lin, Shang-Hsien Hsieh Pages 238-245 (2023 Proceedings of the 40th ISARC, Chennai, India, ISBN 978-0-6458322-0-4, ISSN 2413-5844) Abstract: In construction, project schedules are still created and updated manually, which takes time, causes errors, and leads to poor planning and scheduling, one of the main reasons for project delays today. Consequently, overcoming these challenges requires an automated schedule management method that extracts information and knowledge from existing and previous databases to improve construction planning and scheduling. Natural Language Processing (NLP) and Building Information Modeling (BIM) are two technologies that can revolutionize construction planning and scheduling by providing the ability to extract and interpret data from project documents, models, and past project knowledge bases. This paper reviews the state-of-the-art to understand the current research and methods that use NLP and BIM to automate construction schedule management (CSM). This in-depth study examines the knowledge potential of both technologies and integration possibilities in the construction planning and scheduling context. It also highlights the popular methods in recent times, a generalized workflow of NLP-based data processing, and limitations of existing approaches in practical applications. Finally, this study introduces three future research directions for integrating BIM and NLP for automated CSM. Keywords: Natural Language Processing, Building Information Modeling, Construction Planning and Scheduling, Data Extraction, Information Retrieval, Optimization, ChatGPT. DOI: https://doi.org/10.22260/ISARC2023/0034 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley Presentation Video: https://youtu.be/dZDKJb6NYqw