Big Data in the construction industry: A review of present status, opportunities, and future trends

Muhammad Bilal; Lukumon O. Oyedele; Junaid Qadir; Kamran Munir; Saheed O. Ajayi; Olugbenga O. Akinade; Hakeem A. Owolabi; Hafiz A. Alaka; Maruf Pasha

doi:10.1016/j.aei.2016.07.001

Big Data in the construction industry: A review of present status, opportunities, and future trends

Muhammad Bilal, Lukumon O. Oyedele, Junaid Qadir, Kamran Munir, Saheed O. Ajayi, Olugbenga O. Akinade, Hakeem A. Owolabi, Hafiz A. Alaka, Maruf Pasha

Research output: Contribution to journal › Review article › peer-review

503 Citations (Scopus)

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Abstract

The ability to process large amounts of data and to extract useful insights from data has revolutionised society. This phenomenon—dubbed as Big Data—has applications for a wide assortment of industries, including the construction industry. The construction industry already deals with large volumes of heterogeneous data; which is expected to increase exponentially as technologies such as sensor networks and the Internet of Things are commoditised. In this paper, we present a detailed survey of the literature, investigating the application of Big Data techniques in the construction industry. We reviewed related works published in the databases of American Association of Civil Engineers (ASCE), Institute of Electrical and Electronics Engineers (IEEE), Association of Computing Machinery (ACM), and Elsevier Science Direct Digital Library. While the application of data analytics in the construction industry is not new, the adoption of Big Data technologies in this industry remains at a nascent stage and lags the broad uptake of these technologies in other fields. To the best of our knowledge, there is currently no comprehensive survey of Big Data techniques in the context of the construction industry. This paper fills the void and presents a wide-ranging interdisciplinary review of literature of fields such as statistics, data mining and warehousing, machine learning, and Big Data Analytics in the context of the construction industry. We discuss the current state of adoption of Big Data in the construction industry and discuss the future potential of such technologies across the multiple domain-specific sub-areas of the construction industry. We also propose open issues and directions for future work along with potential pitfalls associated with Big Data adoption in the industry.

Original language	English
Pages (from-to)	500-521
Number of pages	22
Journal	Advanced Engineering Informatics
Volume	30
Issue number	3
DOIs	https://doi.org/10.1016/j.aei.2016.07.001
Publication status	Published - 19 Jul 2016
Externally published	Yes

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in Advanced Engineering Informatics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Advanced Engineering Informatics, [3, 30, (2016)] DOI: 10.1016/j.aei.2016.07.001

© 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

Big Data Analytics
Big Data Engineering
Construction industry
Machine learning

ASJC Scopus subject areas

Information Systems
Artificial Intelligence

Access to Document

10.1016/j.aei.2016.07.001

Post-PrintAccepted author manuscript, 1.29 MBLicence: CC BY-NC-ND

https://uwe-repository.worktribe.com/output/909586/big-data-in-the-construction-industry-a-review-of-present-status-opportunities-and-future-trends

Cite this

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title = "Big Data in the construction industry: A review of present status, opportunities, and future trends",

abstract = "The ability to process large amounts of data and to extract useful insights from data has revolutionised society. This phenomenon—dubbed as Big Data—has applications for a wide assortment of industries, including the construction industry. The construction industry already deals with large volumes of heterogeneous data; which is expected to increase exponentially as technologies such as sensor networks and the Internet of Things are commoditised. In this paper, we present a detailed survey of the literature, investigating the application of Big Data techniques in the construction industry. We reviewed related works published in the databases of American Association of Civil Engineers (ASCE), Institute of Electrical and Electronics Engineers (IEEE), Association of Computing Machinery (ACM), and Elsevier Science Direct Digital Library. While the application of data analytics in the construction industry is not new, the adoption of Big Data technologies in this industry remains at a nascent stage and lags the broad uptake of these technologies in other fields. To the best of our knowledge, there is currently no comprehensive survey of Big Data techniques in the context of the construction industry. This paper fills the void and presents a wide-ranging interdisciplinary review of literature of fields such as statistics, data mining and warehousing, machine learning, and Big Data Analytics in the context of the construction industry. We discuss the current state of adoption of Big Data in the construction industry and discuss the future potential of such technologies across the multiple domain-specific sub-areas of the construction industry. We also propose open issues and directions for future work along with potential pitfalls associated with Big Data adoption in the industry.",

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note = "NOTICE: this is the author{\textquoteright}s version of a work that was accepted for publication in Advanced Engineering Informatics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Advanced Engineering Informatics, [3, 30, (2016)] DOI: 10.1016/j.aei.2016.07.001 {\textcopyright} 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/",

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AU - Bilal, Muhammad

AU - Oyedele, Lukumon O.

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AU - Munir, Kamran

AU - Ajayi, Saheed O.

AU - Akinade, Olugbenga O.

AU - Owolabi, Hakeem A.

AU - Alaka, Hafiz A.

AU - Pasha, Maruf

N1 - NOTICE: this is the author’s version of a work that was accepted for publication in Advanced Engineering Informatics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Advanced Engineering Informatics, [3, 30, (2016)] DOI: 10.1016/j.aei.2016.07.001 © 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

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N2 - The ability to process large amounts of data and to extract useful insights from data has revolutionised society. This phenomenon—dubbed as Big Data—has applications for a wide assortment of industries, including the construction industry. The construction industry already deals with large volumes of heterogeneous data; which is expected to increase exponentially as technologies such as sensor networks and the Internet of Things are commoditised. In this paper, we present a detailed survey of the literature, investigating the application of Big Data techniques in the construction industry. We reviewed related works published in the databases of American Association of Civil Engineers (ASCE), Institute of Electrical and Electronics Engineers (IEEE), Association of Computing Machinery (ACM), and Elsevier Science Direct Digital Library. While the application of data analytics in the construction industry is not new, the adoption of Big Data technologies in this industry remains at a nascent stage and lags the broad uptake of these technologies in other fields. To the best of our knowledge, there is currently no comprehensive survey of Big Data techniques in the context of the construction industry. This paper fills the void and presents a wide-ranging interdisciplinary review of literature of fields such as statistics, data mining and warehousing, machine learning, and Big Data Analytics in the context of the construction industry. We discuss the current state of adoption of Big Data in the construction industry and discuss the future potential of such technologies across the multiple domain-specific sub-areas of the construction industry. We also propose open issues and directions for future work along with potential pitfalls associated with Big Data adoption in the industry.

AB - The ability to process large amounts of data and to extract useful insights from data has revolutionised society. This phenomenon—dubbed as Big Data—has applications for a wide assortment of industries, including the construction industry. The construction industry already deals with large volumes of heterogeneous data; which is expected to increase exponentially as technologies such as sensor networks and the Internet of Things are commoditised. In this paper, we present a detailed survey of the literature, investigating the application of Big Data techniques in the construction industry. We reviewed related works published in the databases of American Association of Civil Engineers (ASCE), Institute of Electrical and Electronics Engineers (IEEE), Association of Computing Machinery (ACM), and Elsevier Science Direct Digital Library. While the application of data analytics in the construction industry is not new, the adoption of Big Data technologies in this industry remains at a nascent stage and lags the broad uptake of these technologies in other fields. To the best of our knowledge, there is currently no comprehensive survey of Big Data techniques in the context of the construction industry. This paper fills the void and presents a wide-ranging interdisciplinary review of literature of fields such as statistics, data mining and warehousing, machine learning, and Big Data Analytics in the context of the construction industry. We discuss the current state of adoption of Big Data in the construction industry and discuss the future potential of such technologies across the multiple domain-specific sub-areas of the construction industry. We also propose open issues and directions for future work along with potential pitfalls associated with Big Data adoption in the industry.

KW - Big Data Analytics

KW - Big Data Engineering

KW - Construction industry

KW - Machine learning

U2 - 10.1016/j.aei.2016.07.001

DO - 10.1016/j.aei.2016.07.001

M3 - Review article

AN - SCOPUS:84978529080

SN - 1474-0346

VL - 30

SP - 500

EP - 521

JO - Advanced Engineering Informatics

JF - Advanced Engineering Informatics

IS - 3

ER -

Big Data in the construction industry: A review of present status, opportunities, and future trends

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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Cite this