Arashpour, Mehrdad

Lee, Yee Sye

Rahimian, Farzad

Rashidi, Ali

Talei, Amin

English

PurposeIn recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The primary aim of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.Design/methodology/approachThis study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.FindingsThe proposed research directions can be categorized into four areas, including 1) Realism of training simulations; 2) Integration of visual and audio-based classification; 3) Automated hazard detection in head-mounted displays (HMDs); and 4) Context-awareness in head-mounted displays (HMDs).Originality/valueThis study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.<br/

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Integration of Deep Learning and Extended Reality Technologies in Construction Engineering and Management: A Mixed Review Method

https://research.tees.ac.uk/files/37072220/Integration_of_Deep_Learning_and_Extended_Reality_Technologies_in_Construction_Engineering_and_Management.PDF

Integration of Deep Learning and Extended Reality Technologies in Construction Engineering and Management: A Mixed Review Method

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Teeside University's Research Repository