Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10722
Title: Proactive training system for safe and efficient precast installation
Authors: Li, H 
Lu, M
Chan, G
Skitmore, M
Keywords: Building Information Models
Construction safety
Construction training
Real-time location system
Work efficiency
Issue Date: 2015
Publisher: Elsevier
Source: Automation in construction, 2015, v. 49, no. PA, p. 163-174 How to cite?
Journal: Automation in construction 
Abstract: The construction industry is a crucial component of the Hong Kong economy, and the safety and efficiency of workers are two of its main concerns. The current approach to training workers relies primarily on instilling practice and experience in conventional teacher-apprentice settings on and off site. Both have their limitations however, on-site training is very inefficient and interferes with progress on site, while off-site training provides little opportunity to develop the practical skills and awareness needed through hands-on experience. A more effective way is to train workers in safety awareness and efficient working by current novel information technologies. This paper describes a new and innovative prototype system - the Proactive Construction Management System (PCMS) - to train precast installation workers to be highly productive while being fully aware of the hazards involved. PCMS uses Chirp-Spread-Spectrum-based (CSS) real-time location technology and Unity3D-based data visualisation technology to track construction resources (people, equipment, materials, etc.) and provide real-time feedback and post-event visualisation analysis in a training environment. A trial of a precast facade installation on a real site demonstrates the benefits gained by PCMS in comparison with equivalent training using conventional methods. It is concluded that, although the study is based on specific industrial conditions found in Hong Kong construction projects, PCMS may well attract wider interest and use in future.
URI: http://hdl.handle.net/10397/10722
ISSN: 0926-5805
EISSN: 1872-7891
DOI: 10.1016/j.autcon.2014.10.010
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

22
Last Week
1
Last month
2
Citations as of Nov 8, 2018

WEB OF SCIENCETM
Citations

17
Last Week
0
Last month
0
Citations as of Nov 9, 2018

Page view(s)

71
Last Week
2
Last month
Citations as of Nov 12, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.