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Proceedings Paper

Accident patterns for construction-related workers: a cluster analysis
Author(s): Chia-Wen Liao; Yaw-Yauan Tyan
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Paper Abstract

The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

Paper Details

Date Published: 13 January 2012
PDF: 5 pages
Proc. SPIE 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, 834936 (13 January 2012); doi: 10.1117/12.920951
Show Author Affiliations
Chia-Wen Liao, China Univ. of Technology (Taiwan)
Yaw-Yauan Tyan, China Univ. of Technology (Taiwan)


Published in SPIE Proceedings Vol. 8349:
Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis
Zhu Zeng; Yuting Li, Editor(s)

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