CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

PDF papers
id ecaade2014_111
authors Fabian Danker and Oliver Jones
year 2014
title Combining Augmented Reality and Building Information Modelling - An industry perspective on applications and future directions.
source Thompson, Emine Mine (ed.), Fusion - Proceedings of the 32nd eCAADe Conference - Volume 2, Department of Architecture and Built Environment, Faculty of Engineering and Environment, Newcastle upon Tyne, England, UK, 10-12 September 2014, pp. 525-536
summary The aim of this paper is to investigate the applications both current and potential, of combining Augmented Reality (AR) and Building Information Modelling (BIM), providing an insight into attitudes towards utilising these technologies within the construction industry. This paper presents a study which has evaluated current research on the topic of AR and BIM, conducted semi structured interviews with a panel of industry experts and surveyed a sample group of 43 within the wider UK construction industry . Industry experts were interviewed using semi-structured interviews and results were thematically analysed with the data gathered from the literature review. 5 core themes used to structure a nine item industry and practitioner questionnaire. Results suggest that use of AR and BIM within the construction industry will continue to grow with the advent of emerging technologies. Use of AR and BIM combined with 3D Scanning, Wireless Sensory Network will also increase and the synergies between BIM and these emerging technologies will improve overall efficiencies in design, delivery, maintenance and demolition of projects. The findings of this study contribute further knowledge to understanding the implications and possibilities that utilising AR and BIM will have in the construction industry.
wos WOS:000361385100055
keywords Augmented reality; emerging technologies; building information modelling; aec industry
series eCAADe
full text file.pdf (321,984 bytes)
references Content-type: text/plain
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