A review on BIM-based automated compliance checking

被引：0
|
作者：
Zhou Y. [1 ]
Wang G. [1 ]
Cao D. [1 ]
机构：
[1] Tongji University, Shanghai
来源：
Tumu Gongcheng Xuebao/China Civil Engineering Journal | 2024年 / 57卷 / 04期
关键词：
automated compliance checking; building information model; information extraction; information matching; semantic enrichment;
D O I：
10.15951/j.tmgcxb.22121210
中图分类号：
学科分类号：
摘要：
With the deep application of building information modeling (BIM) technology in the construction field, an increasing number of architectural designs are expressed and delivered in the way of BIM models. BIM-based automated compliance checking (ACC) of architectural design has received more attention in both theory and practice because of its advantages in objectivity and efficiency. This paper reviews the existing studies on BIM-based ACC, and conducts a comprehensive search of related research papers in the core database of Web of Science. The existing studies are summarized from five aspects: basic framework of BIM-based ACC, information extraction of regulation provisions, BIM model data extraction and semantic enrichment, regulation-model information matching, and compliance reasoning. The future research trends in above fields are further discussed. Finally, the research points out that BIM-based ACC still faces huge challenges in the performance and depth of complex text information extraction, model semantic enrichment, the degree of automation and universality of information matching, and the transparency and flexibility of computer code. © 2024 Chinese Society of Civil Engineering. All rights reserved.
引用
收藏
页码：102 / 110
页数：8
相关论文
共 54 条
  • [1] Zhou X P, Zhao J C, Wang J, Et al., Parallel computing-based online geometry triangulation for building information modeling utilizing big data, Automation in Construction, 107, (2019)
  • [2] Eastman C, Lee J M, Jeong Y S, Et al., Automatic rule-based checking of building designs, Automation in Construction, 18, 8, pp. 1011-1033, (2009)
  • [3] Zhou P, El-Gohary N., Ontology-based automated information extraction from building energy conservation codes [J], Automation in Construction, 74, pp. 103-117, (2017)
  • [4] Wang X Y, El-Gohary N., Deep learning-based relation extraction from construction safety regulations for automated field compliance checking [C], Construction Research Congress 2022, (2022)
  • [5] Zhang J S, El-Gohary N M., Integrating semantic NLP and logic reasoning into a unified system for fully-automated code checking[J], Automation in Construction, 73, pp. 45-57, (2017)
  • [6] Zhong B T, Wu H T, Xiang R, Et al., Automatic information extraction from construction quality inspection regulations: a knowledge pattern-based ontological method, Journal of Construction Engineering and Management, 148, 3, (2022)
  • [7] Zhong B T, Ding L Y, Luo H B, Et al., Ontology-based semantic modeling of regulation constraint for automated construction quality compliance checking, Automation in Construction, 28, pp. 58-70, (2012)
  • [8] Zhang J S, El-Gohary N M., Semantic NLP-based information extraction from construction regulatory documents for automated compliance checking [J], Journal of Computing in Civil Engineering, 30, 2, (2016)
  • [9] Zhang J S, El-Gohary N M., Automated information transformation for automated regulatory compliance checking in construction, Journal of Computing in Civil Engineering, 29, 4, (2015)
  • [10] Salama D M, El-Gohary N M., Semantic text classification for supporting automated compliance checking in construction [J], Journal of Computing in Civil Engineering, 30, 1, (2016)
123456