• International conference on construction engineering and project management
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• 2015.10a
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• pp.179-182
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• 2015

Detecting and assessing human-related risks is critical to improve the on-site safety condition and reduce the loss in lives, time and budget for construction industry. Recent research in neural science and psychology suggest inattentional blindness that caused by overload in working memory is the major cause of unexpected human related accidents. Due to the limitation of human mental workload, laborers are vulnerable to unexpected hazards while focusing on complicated and dangerous construction tasks. Therefore, detecting the risk perception abilities of workers could help to identify vulnerable individuals and reduce unexpected injuries. However, there are no available measurement approaches or devices capable of monitoring construction workers' mental conditions. The research proposed in this paper aims to develop such a measurement framework to evaluate hazards through monitoring electroencephalogram of labors. The research team developed a wearable safety monitoring helmet, which can collect the brain waves of users for analysis. A bispectrum approach has been developed in this paper to enrich the data source and improve accuracy.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.5
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• pp.371-376
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• 2016

Safety related workers, such as firefighters, have to wear a protective helmet. The Development of Helmets for safety is in progress to promote the wearable device industry. Several accidents caused by negligence in recent days have raised public attention to safety. For this reason, the amount of national budget funding for the study of fire-fighting and smart safety helmets has increased. However, most previous studies have focused on safety, rather than the application of new technologies based on physical attributes, especially the characteristics of head shape and size, even though fire helmets play the critical role of protection from flames and external shocks etc. in an emergency. This paper will present the smart technologies and newly developed designs for safety helmets that are personalized for each firefighter, based on the characteristics of their head, and will help a rescue operation to be much more safe and efficient.

• Journal of the Korea Institute of Building Construction
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• v.23 no.1
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• pp.81-92
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• 2023

According to the 2020 industrial accident reports of the Ministry of Employment and Labor, the number of fatal accidents in the construction industry over the past 5 years has been higher than in other industries. Of these more than 50% of fatal accidents are initially caused by fall accidents. The central government is intensively managing falling/jamming protection device and the use of personal protective equipment to eradicate the inappropriate factors disrupting safety at construction sites. In addition, although efforts have been made to prevent safety accidents with the proposal of the Special Act on Construction Safety, fatalities on construction sites are constantly occurring. Therefore, this study developed a model that automatically detects the wearing state of the worker's safety helmet and belt using computer vision technology. In considerations of conditions occurring at construction sites, we suggest an optimization method, which has been verified in terms of the accuracy and operation speed of the proposed model. As a result, it is possible to improve the efficiency of inspection and patrol by construction site managers, which is expected to contribute to reinforcing competency of safety management.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.28-36
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• 2022

Currently, the automation and intelligence of the shipbuilding industry have improved its work production capacity and cost competitiveness, but the reduction rate of safety accidents among industrial site workers is still low and the damage caused by safety accidents is very serious, so there is a need for improvement according to the workplace. This research aims to demonstrate the connectivity between smart safety helmets in the demonstration area to verify the effectiveness along with the development of smart helmets for worker protection and environmental safety in shipyards. For efficient communication between workers, impact noise of over 95dB was confirmed in the workplace, and noise reduction was required. To solve this problem, the filtering performance was compared and analyzed using the Butterworth, Chebyshev, and elliptic algorithms. The connectivity test and noise reduction method between smart helmets proposed in this study will increase the usability and safety of the field through the development of advanced smart helmets tailored to the shipbuilding workplace in the future.

• Journal of Environmental Health Sciences
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• v.39 no.6
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• pp.522-531
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• 2013

Objectives: A field survey was conducted in a hog-raising industry in order to help develop personal protective equipment for workers which would secure the safety and the health of these workers. The attempt by this study will help enhance safety in the livestock industry and contribute to the advancement of the industry. Method: The study first selected a total of 111 workers from the hog-raising industry as research participants and designed a survey with questions on general characteristics, indoor and outdoor working environments, how the workers would in practice wear or purchase the working clothes, what needs to be improved in these new working clothes, how much the workers would be likely to accept the working clothes and protective equipment, and lastly, conditions of the communicable disease control overgarment. The collected data underwent frequency analysis and cross analysis with SPSS 21.0. Result: The research targets' average age was 50 years. Work efficiency by environmental factor was normal, but all age groups had experience of accidents (79.3%). Major wounded parts were under elbow and under knee. Protective equipment most commonly worn was helmet (83.4%), gloves (98.2%) and boots (99.1%), and satisfaction with them was normal at 3.41. Working clothing most commonly worn was old clothing (31.8%) and everyday wear (17.6%) and satisfaction with it was low. Considering the improvement of working clothing, they required attached pouches, elasticity and deodorization. The acceptability of improved working clothing was high at 69.2%. Conclusion: After problems have been addressed in relevant future research, what has been learned from the concerned study will be referred to as a useful basic reference when the relevant field works to develop high-quality working clothing and protective equipment for workers in the hog-raising industry.

• Journal of the Korean Society of Safety
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• v.23 no.6
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• pp.21-27
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• 2008

Polypropylene(PP) foams are widely used as protective materials such as automotive bumper and safety helmet, but whose dynamic behaviour are not well defined. In this paper, the compression tests by Split Hopkinson Pressure Bar were conducted to obtain the stress-strain curve and to investigate the effect of density on the absorption of impact energy in the PP foams. Three kinds of foams were chosen depending upon the density. The result of the experiment has revealed that the stiffness of the low-density PP foam is remarkably increased at high strain rate compared with that of the high-density PP foam. And it is also shown that the absorption of impact energy are greatly influenced by the density of PP foam. These results are expected to be utilized for the development of a protective structure with polymer foams.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.1
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• pp.48-56
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• 2023

This paper implements many-to-many communication between users and develops a multi-functional smart helmet for worker protection and environmental safety in the shipbuilding and shipping industry. First, the communication situation is recorded in the field to perform signal processing for noise that interferes with communication. Then, it deals with the contents of developing smart helmets, data acquisition, algorithms, and simulations. The simulation results analyzed by applying the adaptive algorithm are shown, and their usefulness is confirmed. In conclusion, looking at the optimization process for the convergence factor of the Least Mean Square and Filtered-x Least Mean Square Adaptation Algorithm was possible. It is thought that it has laid the foundation for implementing many-to-many communication, the function of smart helmets that reduces or removes various noises at the shipyard in the future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.61-69
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• 2022

As the delivery industry grew around the restaurant industry along with the COVID-19 situation, the number of delivery workers increased significantly. Along with that, new forms of delivery using personal mobility (PM) also emerged and two-wheeled or PM-related accidents are steadily increasing. This study manufactures a PM's driving analysis device to establish a safe delivery monitoring environment. This system was constructed to process data collected from the driving analysis device and through a cloud server, which would recognize and record special situations (acceleration/deceleration, speed bump) that could occur during the PM's driving situation. As a result, the angular speed, acceleration, and geomagnetic values collected from the IMU in the device were able to determine whether to drive, drive on the sidewalk, and drive on the speed bump. This technology was able to achieve approximately 1600 times more driving information storage efficiency than conventional image-based recording devices.