Litcius/Paper detail

Application of artificial intelligence and machine learning for BIM: review

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

2023International Journal for Simulation and Multidisciplinary Design Optimization55 citationsDOIOpen Access PDF

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.

Topics & Concepts

Building information modelingWorkflowDomain (mathematical analysis)Field (mathematics)Quality (philosophy)Computer scienceControl (management)LandscapingSystems engineeringEngineeringArtificial intelligenceDatabaseScheduling (production processes)Operations managementMathematical analysisBotanyBiologyPure mathematicsMathematicsEpistemologyPhilosophyBIM and Construction IntegrationInfrastructure Maintenance and Monitoring3D Surveying and Cultural Heritage