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Journal of Construction Engineering
Volume 2015 (2015), Article ID 721380, 8 pages
http://dx.doi.org/10.1155/2015/721380
Research Article

Hard-Hat Detection for Construction Safety Visualization

1Department of Civil and Environmental Engineering and Construction, Howard R. Hughes College of Engineering, University of Nevada, Las Vegas, NV 89154, USA
2Cerner Corporation World, Kansas City, MO 64117, USA
3Department of Computer Science, Howard R. Hughes College of Engineering, University of Nevada, Las Vegas, NV 89154, USA

Received 30 September 2014; Accepted 17 January 2015

Academic Editor: F. Pacheco-Torgal

Copyright © 2015 Kishor Shrestha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In 2012, 775 fatalities were recorded, and many more were injured at construction sites in the United States. Of these, 415 fatalities (54%) were due to fall, slips, and trips as well as being struck by falling objects. In order to decrease fatalities at construction sites to these types of events, the Occupational Safety and Health Administration (OSHA) provides Fall Prevention and OSHA-10 trainings to construction workers. Moreover, safety personnel monitor whether the workers use personal protective equipment (PPE) properly. Data shows that construction fatalities have decreased by 2% annually since 1994; however, the owners still are not satisfied with this result. Various studies have shown that fall is the biggest contributor for construction fatalities. One study showed that half of the fall fatalities were because the workers either had not used PPEs or had not used them properly. In addition, studies showed that, with proper use of hard hats, the fatalities due to fall, slips, trips, and being struck by falling objects could be reduced. This study developed and tested a hard-hat detection tool that uses image-processing techniques to identify whether workers are wearing hard hats. The tool dispatches warning messages if the workers do not use hard hats.