Application of artificial intelligence and machine learning for BIM: review

Q3 Mathematics

International Journal for Simulation and Multidisciplinary Design Optimization Pub Date : 2023-01-01 DOI:10.1051/smdo/2023005

David Bassir, Hugo Lodge, Haochen Chang, Jüri Majak, Gongfa Chen

引用次数: 2

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.

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人工智能和机器学习在BIM中的应用:综述

在建筑信息模型(BIM)工作流程中，质量控制是一个非常重要的方面。无论在生命周期的哪个阶段，获得并遵循构建指标都是很重要的。BIM是一个非常消耗数据的领域，从图像处理到大数据分析，这些数据的分析需要先进的数值工具。人工智能(AI)和机器学习(ML)已经证明了它们在处理自动化流程和提取不同行业有用数据源方面的效率。除了指标跟踪之外，AI和ML还可以很好地预测何时何地提供维护和/或质量控制。在这篇文章中，将介绍人工智能和机器学习在BIM中的应用。还将讨论进一步的建议和挑战。其目的是提供当今建筑和景观领域的需求知识，并就这些技术如何影响工业和未来的研究提供广泛的理解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal for Simulation and Multidisciplinary Design Optimization Mathematics-Control and Optimization

CiteScore

2.00

自引率

0.00%

发文量

审稿时长

16 weeks

期刊介绍： The International Journal for Simulation and Multidisciplinary Design Optimization is a peer-reviewed journal covering all aspects related to the simulation and multidisciplinary design optimization. It is devoted to publish original work related to advanced design methodologies, theoretical approaches, contemporary computers and their applications to different fields such as engineering software/hardware developments, science, computing techniques, aerospace, automobile, aeronautic, business, management, manufacturing,... etc. Front-edge research topics related to topology optimization, composite material design, numerical simulation of manufacturing process, advanced optimization algorithms, industrial applications of optimization methods are highly suggested. The scope includes, but is not limited to original research contributions, reviews in the following topics: Parameter identification & Surface Response (all aspects of characterization and modeling of materials and structural behaviors, Artificial Neural Network, Parametric Programming, approximation methods,…etc.) Optimization Strategies (optimization methods that involve heuristic or Mathematics approaches, Control Theory, Linear & Nonlinear Programming, Stochastic Programming, Discrete & Dynamic Programming, Operational Research, Algorithms in Optimization based on nature behaviors,….etc.) Structural Optimization (sizing, shape and topology optimizations with or without external constraints for materials and structures) Dynamic and Vibration (cover modelling and simulation for dynamic and vibration analysis, shape and topology optimizations with or without external constraints for materials and structures) Industrial Applications (Applications Related to Optimization, Modelling for Engineering applications are very welcome. Authors should underline the technological, numerical or integration of the mentioned scopes.).