Building Information Modeling and Its Applications Based on Machine Learning

Pouya Ghanizadeh Anganeh¹ Iman Bagheri²

1) Department of Architecture and Urbanism, Tabriz Branch, Islamic Azad University, Tabriz, Iran
2) ECE Department, Montazeri Technical and Vocational University, Mashhad, Iran Email:

Publication : 2nd International Congress on Science, engineering & New Technologies(secongress.com)
Abstract :
BIM systems not only generate and store data but also adapt to the changing project lifecycle requirements. This enables project knowledge to be continuously evaluated and extracted, from the earliest stages of inception to completion. Thanks to the advancements in machine learning (ML), this data can now be harnessed to improve process automation and knowledge acquisition across various industries and data sources. However, for the Architecture, Engineering, Construction, and Operations (AECO) sector, adopting and effectively utilizing ML techniques in BIM-based projects presents its own unique set of challenges. These include the rapidly evolving landscape of ML applications, the abundance of BIM-related data being generated, and the diverse applications for this data. Although the study of ML applications to BIM data has been increasing for a decade, they are still relatively new. In order to assess the current state of the market, this study utilizes a systematic literature review (SLR) to identify and describe new ML applications and their utilization in building information models (BIMs). The report not only evaluates current trends but also identifies research gaps that need further exploration. These gaps include scalability of applications, human interactions with information, as well as information architecture and data, all of which were revealed as limitations in the research.
Keywords : BIM Building Management Machine Learning AI BIM Applications