The ability to process large amounts of data and 1 to extract useful insights from data has revolutionised society. 2 This phenomenon-dubbed as Big Data-has applications for a 3 wide assortment of industries, including the construction industry. 4 The construction industry already deals with large volumes of 5 heterogeneous data; which is expected to increase exponentially 6 as technologies such as sensor networks and the Internet of 7 Things are commoditized. In this paper, we present a detailed 8 survey of the literature, investigating the application of Big Data 9 techniques in the construction industry. We reviewed related 10 works published in the databases of American Association of 11 Civil Engineers (ASCE), Institute of Electrical and Electronics 12 Engineers (IEEE), Association of Computing Machinery (ACM), 13 and Elsevier Science Direct Digital Library. While the application 14 of data analytics in the construction industry is not new, the 15 adoption of Big Data technologies in this industry remains at a 16 nascent stage and lags the broad uptake of these technologies in 17 other fields. To the best of our knowledge, there is currently no 18 comprehensive survey of Big Data techniques in the context of 19 the construction industry. This paper fills the void and presents a 20 wide-ranging interdisciplinary review of literature of fields such 21 as statistics, data mining and warehousing, machine learning, and 22 Big Data Analytics in the context of the construction industry. 23 We discuss the current state of adoption of Big Data in the 24 construction industry and discuss the future potential of such 25 technologies across the multiple domain-specific sub-areas of the 26 construction industry. We also propose open issues and directions 27 for future work along with potential pitfalls associated with Big 28 Data adoption in the industry. 29 I. INTRODUCTION 30 The world is currently inundated with data, with fast advanc-31 ing technology leading to its steady increase. Today, companies 32 deal with petabytes (10 15 bytes) of data. Google processes 33 above 24 petabytes of data per day [1], while Facebook gets 34 more than 10 million photos per hour [1]. The glut of data 35 increased in 2012 is approximately 2.5 quintillion (10 18) bytes 36 per day [2]. This data growth brings significant opportunities 37 to scientists for identifying useful insights and knowledge. 38 Arguably, the accessibility of data can improve the status 39 quo in various fields by strengthening existing statistical and 40 algorithmic methods [3], or by even making them redundant 41 [4]. 42 The construction industry is not an exception to the per-43 vasive digital revolution. The industry is dealing with sig-44 nificant data arising from diverse disciplines throughout the 45 life cycle of a facility. Building Information Modelling (BIM) 46 is envisioned to capture multi-dimensional CAD information 47 systematically for supporting multidisciplinary collaboration 48 among the stakeholders [5]. BIM data is typically 3D ge-49 ometric enc...

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15Construction industry contributes a large portion of waste to landfill, which in turns results in

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