Safety Helmet Wearing Management System for Construction Workers Using Three-Axis Accelerometer Sensor

• Main Authors: Sung Hun Kim, Changwon Wang, Se Dong Min, Seung Hyun Lee
• Format: Article
• Language: English
• Published: MDPI AG 2018-11-01
• Series: Applied Sciences
• Subjects: construction; worker safety; safety helmet; three-axis accelerometer sensor; data mining
• Online Access: https://www.mdpi.com/2076-3417/8/12/2400

In the Korean construction industry, legal and institutional safety management improvements are continually being pursued. However, there was a 4.5% increase in the number of workers’ deaths at construction sites in 2017 compared to the previous year. Failure to wear safety helmets seems to be one of the major causes of the increase in accidents, and so it is necessary to develop technology to monitor whether or not safety helmets are being used. However, the approaches employed in existing technical studies on this issue have mainly involved the use of chinstrap sensors and have been limited to the problem of whether or not safety helmets are being worn. Meanwhile, improper wearing, such as when the chinstrap and harness fixing of the safety helmet are not properly tightened, has not been monitored. To remedy this shortcoming, a sensing safety helmet with a three-axis accelerometer sensor attached was developed in this study. Experiments were performed in which the sensing data were classified whether the safety helmet was being worn properly, not worn, or worn improperly during construction workers’ activities. The results verified that it is possible to differentiate among wearing status of the proposed safety helmet with a high accuracy of 97.0%.