ITcon Vol. 28, pg. 1-18, http://www.itcon.org/2023/1

Invariant Signature, Logic Reasoning, and Semantic Natural Language Processing (NLP)-Based Automated Building Code Compliance Checking (I-SNACC) Framework

DOI:10.36680/j.itcon.2023.001
submitted:July 2021
revised:January 2023
published:January 2023
editor(s):Robert Amor
authors:Jin Wu, Ph.D.
Automation and Intelligent Construction (AutoIC) Lab, School of Construction Management Technology, Purdue University, West Lafayette, IN, 47907, United States
wu1275@purdue.edu

Xiaorui Xue, Ph.D.
Automation and Intelligent Construction (AutoIC) Lab, School of Construction Management Technology, Purdue University, West Lafayette, IN, 47907, United States
xue39@purdue.edu

Jiansong Zhang, Ph.D.
Automation and Intelligent Construction (AutoIC) Lab, School of Construction Management Technology, Purdue University, West Lafayette, IN, 47907, United States
zhan3062@purdue.edu (*corresponding author)
summary:Traditional manual building code compliance checking is costly, time-consuming, and human error-prone. With the adoption of Building Information Modeling (BIM), automation in such a checking process becomes more feasible. However, existing methods still face limited automation when applied to different building codes. To address that, in this paper, the authors proposed a new framework that requires minimal input from users and strives for full automation, namely, the Invariant signature, logic reasoning, and Semantic Natural language processing (NLP)-based Automated building Code compliance Checking (I-SNACC) framework. The authors developed an automated building code compliance checking (ACC) prototype system under this framework and tested it on Chapter 10 of the International Building Codes 2015 (IBC 2015). The system was tested on two real projects and achieved 95.2% precision and 100% recall in non-compliance detection. The experiment showed that the framework is promising in building code compliance checking. Compared to the state-of-the-art methods, the new framework increases the degree of automation and saves manual efforts for finding non-compliance cases.
keywords:Automated Compliance Checking, Building Codes, Invariant Signature, Building Information Modeling (BIM), Natural Language Processing, Logic Reasoning
full text: (PDF file, 0.884 MB)
citation:Wu J, Xue X, Zhang J (2023). Invariant Signature, Logic Reasoning, and Semantic Natural Language Processing (NLP)-Based Automated Building Code Compliance Checking (I-SNACC) Framework, ITcon Vol. 28, Special issue The Eastman Symposium, pg. 1-18, https://doi.org/10.36680/j.itcon.2023.001
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