Skip to main content

Research Repository

Advanced Search

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

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

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


Authors

Muhammad Bilal

Lukumon Oyedele L.Oyedele@uwe.ac.uk
Professor in Enterprise & Project Management

Junaid Qadir

Saheed O. Ajayi

Olugbenga Akinade Olugbenga.Akinade@uwe.ac.uk
Associate Professor - AR/VR Development with Artificial Intelligence

Hakeem Owolabi Hakeem.Owolabi@uwe.ac.uk
Associate Professor - Project Analytics and Digital Enterprise

Hafiz A. Alaka

Maruf Pasha



Abstract

© 2016 Elsevier Ltd 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.

Journal Article Type Review
Acceptance Date Jul 6, 2016
Online Publication Date Jul 19, 2016
Publication Date Aug 1, 2016
Deposit Date Oct 24, 2016
Publicly Available Date Jul 19, 2017
Journal Advanced Engineering Informatics
Print ISSN 1474-0346
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 30
Issue 3
Pages 500-521
DOI https://doi.org/10.1016/j.aei.2016.07.001
Keywords big data engineering, big data analytics, construction industry, machine learning
Public URL https://uwe-repository.worktribe.com/output/909586
Publisher URL http://dx.doi.org/10.1016/j.aei.2016.07.001
Contract Date Oct 24, 2016

Files






You might also like



Downloadable Citations