A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Integration of Deep Learning and Extended Reality Technologies in Construction Engineering and Management: A Mixed Review Method
Purpose In 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/approach This 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. Findings The 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/value This 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.
Integration of Deep Learning and Extended Reality Technologies in Construction Engineering and Management: A Mixed Review Method
Purpose In 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/approach This 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. Findings The 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/value This 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.
Integration of Deep Learning and Extended Reality Technologies in Construction Engineering and Management: A Mixed Review Method
Lee, Yee Sye (author) / Rashidi, Ali (author) / Talei, Amin (author) / Arashpour, Mehrdad (author) / Rahimian, Farzad (author)
2022-04-29
Lee , Y S , Rashidi , A , Talei , A , Arashpour , M & Rahimian , F 2022 , ' Integration of Deep Learning and Extended Reality Technologies in Construction Engineering and Management: A Mixed Review Method ' , Construction Innovation .
Article (Journal)
Electronic Resource
English
DDC:
690
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