Implications of Machine Learning Integrated Technologies for Construction Progress Detection Under Industry 4.0 (IR 4.0)

Qureshi, Abdul Hannan; Alaloul, Wesam Salah; Manzoor, Bilal; Musarat, Muhammad Ali; Saad, Syed; Ammad, Syed

doi:10.1109/ieeeconf51154.2020.9319974

Cited by 30 publications

(24 citation statements)

References 34 publications

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“…However, very limited studies had been conducted on strategies implemented by educators to promote BIM education, which is not only beneficial for the AEC industry but also for BIM experts, developers and researchers [ 80 , 81 ]. Therefore, more proactive collaborations and BIM courses in civil engineering curriculum design are required to advance BIM educators and BIM talent development in the AEC industry [ 82 , 83 ].…”

Section: Resultsmentioning

confidence: 99%

Digital Technologies in the Architecture, Engineering and Construction (AEC) Industry—A Bibliometric—Qualitative Literature Review of Research Activities

Manzoor

Othman

Pomares

2021

IJERPH

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Digital technologies (DTs) are proven helpful in the Architecture, Engineering and Construction (AEC) industry due to their varied benefits to project stakeholders, such as enhanced visualization, better data sharing, reduction in building waste, increased productivity, sustainable performance and safety improvement. Therefore, researchers have conducted various studies on DTs in the AEC industry over the year; however, this study explores the state-of-the-art research on DTs in the AEC industry by means of a bibliometric-qualitative review method. This research would uncover new knowledge gaps and practical needs in the domain of DTs in the AEC industry. In addition, bibliometric analysis was carried out by utilizing academic publications from Scopus (i.e., 11,047 publications for the AEC industry, 1956 for DTs and 1778 for DTs in the AEC industry). Furthermore, a qualitative review was further conducted on 200 screened selected research publications in the domain of DTs. This study brings attention to the body of knowledge by envisioning trends and patterns by defining key research interests, journals, countries, new advancements, challenges, negative attitudes and future directions towards DTs in the AEC industry. However, this study is the first in its vital importance and uniqueness by providing a broad updated review of DTs in the AEC literature. Furthermore, this research laid a foundation for future researchers, policy makers and practitioners to explore the limitations in future research.

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Section: Resultsmentioning

confidence: 99%

Digital Technologies in the Architecture, Engineering and Construction (AEC) Industry—A Bibliometric—Qualitative Literature Review of Research Activities

Manzoor

Othman

Pomares

2021

IJERPH

Self Cite

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“…Although the automation of construction projects remains a future goal, the integration of different ML algorithms is already underway. Managing costs, timelines, and human resources on a construction project are areas guided by various algorithms and computational models [116]. The ML approach can also be applied to develop leading indicators to classify sites according to their safety risk in construction projects.…”

Section: Machine Learning Techniquesmentioning

confidence: 99%

Big Data in Construction: Current Applications and Future Opportunities

Munawar

Ullah

Qayyum

et al. 2022

BDCC

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Big data have become an integral part of various research fields due to the rapid advancements in the digital technologies available for dealing with data. The construction industry is no exception and has seen a spike in the data being generated due to the introduction of various digital disruptive technologies. However, despite the availability of data and the introduction of such technologies, the construction industry is lagging in harnessing big data. This paper critically explores literature published since 2010 to identify the data trends and how the construction industry can benefit from big data. The presence of tools such as computer-aided drawing (CAD) and building information modelling (BIM) provide a great opportunity for researchers in the construction industry to further improve how infrastructure can be developed, monitored, or improved in the future. The gaps in the existing research data have been explored and a detailed analysis was carried out to identify the different ways in which big data analysis and storage work in relevance to the construction industry. Big data engineering (BDE) and statistics are among the most crucial steps for integrating big data technology in construction. The results of this study suggest that while the existing research studies have set the stage for improving big data research, the integration of the associated digital technologies into the construction industry is not very clear. Among the future opportunities, big data research into construction safety, site management, heritage conservation, and project waste minimization and quality improvements are key areas.

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“…BIM technology is gaining popularity due to its model-based characteristics and the technology for coordinating the use of building expertise [56]. BIM has many benefits owing to its integration of expertise from design and project participants, which include improving the design efficiency, reducing construction costs, and promoting the sustainability of projects while ensuring that project workers are interconnected and contributing toward accelerating projects and help to maximize project activities [57].…”

Section: Strategies Referencesmentioning

confidence: 99%

Strategies for Adopting Building Information Modeling (BIM) in Sustainable Building Projects—A Case of Malaysia

et al. 2021

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In terms of sustainable growth, Malaysia’s construction industry faces significant challenges, such as construction costs and lack of awareness. To meet these challenges, it is essential to integrate building information modeling (BIM) and sustainable development. As a result, this study aimed to establish strategies for adopting BIM in sustainable building projects. A systematic literature review was performed to classify the strategies to accomplish this aim, followed by a questionnaire survey of 129 construction project stakeholders. Mean score and exploratory factor analysis (EFA) were conducted to explore the detailed influence of BIM adoption strategies in sustainable building projects. The results revealed that “workshops, lectures, and conference events are used to enhance public awareness” and “better information on the costs and benefits of sustainable materials” and “strengthened sustainable development” were the most essential strategies to boost sustainable growth in building projects. Furthermore, EFA was conducted to undertake the group analysis, namely, to identify the standardization-related strategy, economic-related strategy, awareness-related strategy, and environment-related strategy. This study paves the way for future scholars, policymakers, and practitioners to investigate the limitations of future studies.

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Implications of Machine Learning Integrated Technologies for Construction Progress Detection Under Industry 4.0 (IR 4.0)

Cited by 30 publications

References 34 publications

Digital Technologies in the Architecture, Engineering and Construction (AEC) Industry—A Bibliometric—Qualitative Literature Review of Research Activities

Digital Technologies in the Architecture, Engineering and Construction (AEC) Industry—A Bibliometric—Qualitative Literature Review of Research Activities

Big Data in Construction: Current Applications and Future Opportunities

Strategies for Adopting Building Information Modeling (BIM) in Sustainable Building Projects—A Case of Malaysia

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