Paper title: |
BIM Big Data System Architecture for Asset Management: A Conceptual Framework |
Authors: |
Karim Farghaly, Henry Abanda, Christos Vidalakis and Graham Wood |
Summary: |
Effective decision making in the AEC/FM industry has been based increasingly on an exponential growth of data extracted from different sources and technologies. It has been argued that Building Information Modelling (BIM) can handle this information efficiently, acting as a data pool where data can be stored, managed and integrated. Indeed, a BIM platform based on cloud computing and Big Data can manage the storage and flow of data, as well as extract knowledge from Geographical Information Systems (GIS), Internet of Things (IoT), asset management, energy management and materials and resources databases. Furthermore, it can also provide an opportunity for multiple users to view, access and edit the data in 3D environment. This paper describes the requirements and different components of a BIM Big Data platform for facilitating management of building assets. This is achieved by firstly, conducting a critical peer review to ascertain Big Data definitions and stages, and also to define the critical BIM requirements for the Big Data platform. At the crux, this paper presents a conceptual framework for developing a Big Data platform for BIM which incorporates suitable tools and techniques needed to export, store, analyse and visualise BIM data. |
Type: |
regular paper |
Year of publication: |
2017 |
Keywords: |
Building Information Modelling, Big Data, Asset Management |
Series: |
jc3:2017 |
Download paper: |
/pdfs/LC3_2017_paper_163.pdf |
Citation: |
Karim Farghaly, Henry Abanda, Christos Vidalakis and Graham Wood (2017).
BIM Big Data System Architecture for Asset Management: A Conceptual Framework. Lean and Computing in Construction Congress (LC3): Volume I Ð Proceedings of the Joint Conference on Computing in Construction (JC3), July 4-7, 2017, Heraklion, Greece, pp. 289-296,
http://itc.scix.net/paper/lc3-2017-163
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