Building defects are notoriously difficult to identify, even by the most experienced surveyor. Traditional training methods of identifying defects in buildings involved the physical visiting of a property. This has become more difficult as insurance and organisational issues have made this practice unsafe and costly. Methods of training surveyors can be brought up to date with the introduction of desktop technology to provide learners with a rich set of learning resources in a much easier format. Defects generated from real life cases using digital cameras are stored in a format that can be transformed into QuickTime VR movies and then used to train inexperienced surveyors. This paper describes a prototype application using case‐based‐reasoning virtual reality and multimedia authoring technologies. The architecture of the system is described and some details of the methodology used are discussed. An iterative approach is used to develop the system and validate it.
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Technical Paper|
May 01 2000
Learning building pathology using computers – a prototype application Available to Purchase
Mark Shelbourn;
Mark Shelbourn
Mark Shelbourn is studying for a PhD in the Centre for Construction and Property Management at the University of Salford, Salford, UK.
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Ghassan Aouad;
Ghassan Aouad
Ghassan Aouad is a Professor of Information Technology in Construction in the School of Construction and Property Management at the University of Salford, Salford, UK.
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Mike Hoxley;
Mike Hoxley
Mike Hoxley is Senior Lecturer and Course Leader for Building Surveying at Anglia Polytechnic University and the research project initiator.
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Eric Stokes
Eric Stokes
Eric Stokes is a Programme Director, University of Salford, Salford, UK.
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Publisher: Emerald Publishing
Online ISSN: 1758-6844
Print ISSN: 0263-080X
© MCB UP Limited
2000
Structural Survey (2000) 18 (2): 111–119.
Citation
Shelbourn M, Aouad G, Hoxley M, Stokes E (2000), "Learning building pathology using computers – a prototype application". Structural Survey, Vol. 18 No. 2 pp. 111–119, doi: https://doi.org/10.1108/02630800010330167
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