Application of artificial intelligence and machine learning for BIM: review

Author:

Bassir DavidORCID,Lodge Hugo,Chang HaochenORCID,Majak JüriORCID,Chen Gongfa

Abstract

Quality control is very important aspect in Building Information Modelling (BIM) workflows. Whatever stage of the lifecycle it is important to get and to follow building indicators. The BIM it is very data consuming field and analysis of these data require advance numerical tools from image processing to big data analysis. Artificial intelligent (AI) and machine learning (ML) had proven their efficiency to deal with automate processes and extract useful sources of data in different industries. In addition to the indicators tracking, AI and ML can make a good prediction about when and where to provide maintenance and/or quality control. In this article, a review of the AI and ML application in BIM will be presented. Further suggestions and challenges will be also discussed. The aim is to provide knowledge on the needs nowadays into building and landscaping domain, and to give a wide understanding on how those technics would impact industries and future studies.

Funder

This work was supported by the following Project PHC PARROT with grant number (48992SA).

Publisher

EDP Sciences

Subject

Control and Optimization,Modeling and Simulation

Reference45 articles.

1. BIM and Semantic Enrichment Methods and Applications: A Review of Recent Developments

2. Towards digital architecture, engineering, and construction (AEC) industry through virtual design and construction (VDC) and digital twin

3. Building Information Modelling, Artificial Intelligence and Construction Tech

4. Musella C., Serra M., Menna C., Asprone D., BIM & AI: advanced technologies for the digitalisation of seismic damages in masonry buildings (2019) Available at https://www.researchgate.net/publication/336085678_BIM_AI_advanced_technologies_for_ the_digitalisation_of_seismic_damages_in_masonry_buildings

5. Т.Н. Костюнина, Технологии искусственного интеллектавзадачах BIM[C]//BIM-моделирование в задачах строительства и архитектуры. 80–85 (2019)

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3