Image processing and qr code application method for construction safety management

9Citations
Citations of this article
41Readers
Mendeley users who have this article in their library.

Abstract

Construction safety accidents occur due to a combination of factors. Even a minor accident that could have been treated as a simple injury can lead to a serious accident or death, depending on when and where it occurred. Currently, methods for tracking worker behavior to manage such construction safety accidents are being studied. However, applying the methods to the construction site, various additional elements (e.g., sensors, transmitters, wearing equipment, and control systems) that must be additionally installed and managed are required. The cost of installation and management of these factors increases in proportion to the size of the site and the number of targets to be managed. In addition, the application of new equipment and new rules lowers the work efficiency of workers. In this paper, the following contents are described: (1) system overview, (2) image processing-QR code-based safety management target recognition methodology, and (3) object location discrimination technique applying the geometric transformation. Finally, the proposed methodology was tested to confirm the operation in the field, and the experimental results and conclusions were described in the paper.

References Powered by Scopus

You only look once: Unified, real-time object detection

38199Citations
N/AReaders
Get full text

Computer vision techniques for construction safety and health monitoring

446Citations
N/AReaders
Get full text

Overview and analysis of safety management studies in the construction industry

437Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Kim, J. S., Yi, C. Y., & Park, Y. J. (2021). Image processing and qr code application method for construction safety management. Applied Sciences (Switzerland), 11(10). https://doi.org/10.3390/app11104400

Readers' Seniority

Tooltip

Lecturer / Post doc 2

40%

PhD / Post grad / Masters / Doc 2

40%

Researcher 1

20%

Readers' Discipline

Tooltip

Computer Science 4

44%

Engineering 3

33%

Social Sciences 1

11%

Economics, Econometrics and Finance 1

11%

Save time finding and organizing research with Mendeley

Sign up for free