Skip to main content

Research Repository

See what's under the surface

Advanced Search

Analysis of critical features and evaluation of BIM software: Towards a plug-in for construction waste minimization using big data

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

Authors

Lukumon O. Oyedele

Olugbenga O. Akinade

Saheed O. Ajayi

Muhammad Bilal Muhammad.Bilal@uwe.ac.uk
Associate Professor - Big Data Application

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

Junaid Qadir

Saheed Ajayi saheed.ajayi@uwe.ac.uk

Kamran Munir Kamran2.Munir@uwe.ac.uk
Associate Professor in Data Science

Hafiz A. Alaka

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



Abstract

The overall aim of this study is to investigate the potential of Building Information Modelling (BIM) for construction waste minimization. We evaluated the leading BIM design software products and concluded that none of them currently support construction waste minimization. This motivates the development of a plug-in for predicting and minimizing construction waste. After a rigorous literature review and conducting four focused group interviews (FGIs), 12 imperative BIM factors were identified that should be considered for predicting and designing out construction waste. These factors were categorized into four layers, namely the BIM core features layer, the BIM auxiliary features layer, the waste management criteria layer, and the application layer. Further, a process to carry out BIM-enabled building waste analysis (BWA) is proposed. We have also investigated the usage of big data technologies in the context of waste minimization. We highlight that big data technologies are inherently suitable for BIM due to their support of storing and processing large datasets. In particular, the use of graph-based representation, analysis, and visualization can be employed for advancing the state of the art in BIM technology for construction waste minimization.

Journal Article Type Article
Publication Date Jan 1, 2015
Journal International Journal of Sustainable Building Technology and Urban Development
Print ISSN 2093-761X
Publisher Taylor & Francis
Peer Reviewed Peer Reviewed
Volume 6
Issue 4
Pages 211-228
APA6 Citation Bilal, M., Oyedele, L., Qadir, J., Munir, K., Akinade, O., Ajayi, S., …Owolabi, H. A. (2015). Analysis of critical features and evaluation of BIM software: Towards a plug-in for construction waste minimization using big data. International Journal of Sustainable Building Technology and Urban Development, 6(4), 211-228. https://doi.org/10.1080/2093761X.2015.1116415
DOI https://doi.org/10.1080/2093761X.2015.1116415
Keywords BIM, construction waste prediction and minimization, design out waste, waste prevention, big data analytics, NoSQL
Publisher URL http://dx.doi.org/10.1080/2093761X.2015.1116415
Additional Information Additional Information : This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Sustainable Building Technology and Urban Development on 21st January 2016, available online: http://www.tandfonline..../2093761X.2015.1116415.

Files






You might also like



Downloadable Citations

;