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Bakht, M N and El-Diraby, T E (2015) Synthesis of Decision-Making Research in Construction. Journal of Construction Engineering and Management, 141(09).

Francom, T C and El Asmar, M (2015) Project Quality and Change Performance Differences Associated with the Use of Building Information Modeling in Design and Construction Projects: Univariate and Multivariate Analyses. Journal of Construction Engineering and Management, 141(09).

Kim, H, Lee, H, Park, M, Ahn, C R and Hwang, S (2015) Productivity Forecasting of Newly Added Workers Based on Time-Series Analysis and Site Learning. Journal of Construction Engineering and Management, 141(09).

O’Connor, J T, O’Brien, W J and Choi, J O (2015) Standardization Strategy for Modular Industrial Plants. Journal of Construction Engineering and Management, 141(09).

Park, M, Elsafty, N and Zhu, Z (2015) Hardhat-Wearing Detection for Enhancing On-Site Safety of Construction Workers. Journal of Construction Engineering and Management, 141(09).

  • Type: Journal Article
  • Keywords: Occupational safety; Imaging techniques; Automatic identification systems; Information technologies;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000974
  • Abstract:
    Construction is one of the most dangerous job sectors, which annually reports tens of thousands of time-loss injuries and deaths. These injuries and deaths do not only bring suffering to the workers and their families, but also incur delays and costs to the projects. Therefore, safety is an important issue that a general contractor must monitor and control. One of the fundamental safety regulations is wearing a hardhat, which should not be violated anytime on the sites. In this paper, a novel vision-based method is proposed to automate the monitoring of whether people are wearing hardhats on the construction sites. Under the method, human bodies and hardhats are first detected in the video frames captured by on-site construction cameras. Then, the matching between the detected human bodies and hardhats is performed using their geometric and spatial relationship. This way, the people who are not wearing hardhats could be automatically identified and safety alerts could be issued correspondingly. The method has been tested with real site videos. The high safety alert precision and recall of the method demonstrate its potential to facilitate the site safety monitoring work.

Saurin, T A, Formoso, C T, Reck, R, Beck da Silva Etges, B M and Ribeiro, J L D (2015) Findings from the Analysis of Incident-Reporting Systems of Construction Companies. Journal of Construction Engineering and Management, 141(09).

Ye, K, Zhu, W, Shan, Y and Li, S (2015) Effects of Market Competition on the Sustainability Performance of the Construction Industry: China Case. Journal of Construction Engineering and Management, 141(09).