• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.301-304
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• 2022

최근 개인형 이동장치의 사용이 증가하며 이와 관련된 안전문제가 제기 되었다. 그 중 높은 비중을 차지하는 헬멧 미착용에 대해 사용자들에게 헬멧의 거부감을 감소시키고 착용을 장려할 수 있는 서비스를 개발하여 실제 착용률을 증가시키고 사고시 위험 정도를 감소시킬 수 있는 애플리케이션을 설계하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.986-987
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• 2023

본 논문은 신경근육질환 환자의 이동 문제를 해결하고, 기존 전동킥보드 시스템의 한계와 문제점도 해결하는 '신경근육질환 환자를 위한 전동킥보드 안전 환경 시스템'을 제안한다. 주요 특징은 다음과 같다. 첫째, 헬멧 착용 검사를 통과해야만전동킥보드를 이용할 수 있다. 휴대폰 전면 카메라를 통해 사용자의 모습을 촬영하면 딥러닝 모델을 통해 헬멧 착용 여부를 판단한다. 둘째, 주행 금지구역에서는 이용자 추적 모드를 활성화하여 OpenCV를 통해 이용자를 검출및 추적하고이에 따라 모터 PWM을 조절해서 방향 및 속력을 조절함으로써 이용자를 추적한다. 셋째, 헬멧 내 자이로 센서와 쇼크 센서를 통해 주행 사고를 감지하고 SMS를 이용해 해당 보호자에게 자동으로 사고 정보를 전달한다.

• Proceedings of the Optical Society of Korea Conference
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• 2001.02a
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• pp.200-201
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• 2001

헬멧 장착형 HMD(Head-Mounted Display) 시스템은 비행기 조종사나 저격수의 시선을 크게 움직이지 않고 군사 전술상의 현재 상태를 볼 수 있도록 하여 눈의 피로감을 줄이고 시선의 이동에 의한 돌발적인 사고의 위험을 감소시킬 수 있어 군사적으로 유용한 장치이다 HOE(Holographic Optical Element)의 중요한 응용 분야 중 하나로 HMD에서의 결상 렌즈 또는 광 결합기가 있다 HMD 시스템에서 HOE의 역할은 2차원의 단색 디스플레이 영상을 헬멧 착용자의 눈에 반사하여 결상시키는 것이다. (중략)

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.357-358
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• 2016

현재 교통수단으로 이륜차를 타는 사람들이 점점 많아짐에 따라서 도로에서 많은 사고가 발생하여 사망률이 증가하고 있다. 이에 따라서 사망률을 줄이기 위한 해결방법으로 스마트 헬멧을 착용하여 현재 사고자의 위치를 문자 메시지를 통해 경찰이나 병원, 가족들에게 자동으로 문자를 발송하여 현재 위치정보를 파악하여 사망률을 줄이는 것을 목적으로 하고 있다.

• Proceedings of the Korean Reliability Society Conference
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• 2001.06a
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• pp.191-197
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• 2001

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.151-156
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• 2020

The purpose of this study is to design a process for developing wearable sports helmet devices by utilizing IoT server technology, focusing on sports where helmet wear is essential at sports sites. This enables customized training of athletes by continuously accumulating personal biometric information during training, checking players' condition based on data, and informing them of injury prevention and dangerous situations. In addition, the wearable device that can be useful when the training place is likely to damage the physical health due to heat waves or extremes can provide a foundation for improving the performance. Since such technology can be applied not only to the sports field but also to the society such as the industrial field or the underprivileged, it can be expected to be expandable.

• Journal of the Korean Institute of Gas
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• v.12 no.4
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• pp.34-40
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• 2008

Using the finite element method and Taguchi's design technique, the displacement in vertical direction, von Mises stress, and strain energy of the corrugation damper have been analyzed as functions of the extruded length and the thickness of the corrugation damper, and the upper and lower corner radii of the damper. The optimized profile design elements of a corrugation damper are very important for increasing a strain energy absorption capacity of a helmet structure, which is attacked by impulsive external forces. In this study, the optimized design data based on the Taguchi's method was computed as a corrugation damper length of L = 20 mm, a damper thickness of t = 2 mm, the upper corner radius of $R_1=4\;mm$, and the lower corner radius of $R_2=3\;mm$. The optimized design parameters of a corrugation damper indicated that the thickness and extruded length of a corrugation damper may affect to increase the strain energy, which absorbs the impact forces of the helmet.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.150-159
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• 2022

This paper presents an implementation of detecting whether a helmet is worn and there is a fall accident through individual image analysis in real-time from extracting the image objects of several workers active in the industrial field. In order to detect image objects of workers, YOLO, a deep learning-based computer vision model, was used, and for whether a helmet is worn or not, the extracted images with 5,000 different helmet learning data images were applied. For whether a fall accident occurred, the position of the head was checked using the Pose real-time body tracking algorithm of Mediapipe, and the movement speed was calculated to determine whether the person fell. In addition, to give reliability to the result of a falling accident, a method to infer the posture of an object by obtaining the size of YOLO's bounding box was proposed and implemented. Finally, Telegram API Bot and Firebase DB server were implemented for notification service to administrators.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.173-179
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• 2017

Autobike is insufficient of car navigation informations and high of accident dangerousness comparing to car. So if a system providing autobike driver's driving information and e-call function is developed using smart helmet consisting of collision perception sensor, rear camera, bluetooth communication module, MCU and HUD, It is very useful and can decrease of person's damage and handle expeditious traffic accident during autobike accident. In this paper, when this, "Providing system of autobike driver's information and e-call function", software is developed, a proper analysis and design method for practical affairs try to be presented due to showing software development analysis method, architecture of hardware block-diagram, flowchart and UI design.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.386-389
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• 2016

The number of cyclists is on the steady growing for leisure, sports and transportation with the increasing interest in health and environment. However, the number of cycling accidents is also increasing steadily due to the lack of safety awareness and regulations. Focusing on these issues, we propose and develop the smart LED cycling helmet in order to reduce a risk of cycling accident. To provide the motion information of the bicycle for others, we attach the LEDs on the helmet and control the LED lights using Arduino. The motion information is displayed on the LED helmet by using sensors of the smartphone. Communication between Arduino and the smartphone is performed through Bluetooth.