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Applying the Haar-cascade Algorithm for Detecting Safety Equipment in Safety Management Systems for Multiple Working Environments

Department of Chemical Engineering, Yeungnam University, Gyeongsang-si 39541, Korea
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Electronics 2019, 8(10), 1079; https://doi.org/10.3390/electronics8101079
Received: 26 August 2019 / Revised: 18 September 2019 / Accepted: 19 September 2019 / Published: 23 September 2019
(This article belongs to the Section Computer Science & Engineering)
There are many ways to maintain the safety of workers on a working site, such as using a human supervisor, computer supervisor, and smoke–flame detecting system. In order to create a safety warning system for the working site, the machine-learning algorithm—Haar-cascade classifier—was used to build four different classes for safety equipment recognition. Then a proposed algorithm was applied to calculate a score to determine the dangerousness of the current working environment based on the safety equipment and working environment. With this data, the system decides whether it is necessary to give a warning signal. For checking the efficiency of this project, three different situations were installed with this system. Generally, with the promising outcome, this application can be used in maintaining, supervising, and controlling the safety of a worker. View Full-Text
Keywords: Haar–cascade algorithm; safety equipment; safety management system Haar–cascade algorithm; safety equipment; safety management system
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Phuc, L.T.H.; Jeon, H.; Truong, N.T.N.; Hak, J.J. Applying the Haar-cascade Algorithm for Detecting Safety Equipment in Safety Management Systems for Multiple Working Environments. Electronics 2019, 8, 1079.

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