• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.849-856
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• 2020

Recently, as the number of high-height vehicles such as double-decker buses has increased, collision accidents have occurred in bridges and tunnels due to the deviation from the designated routes and driver's carelessness. In the case of the existing front collision warning system, it is limited to vehicles and pedestrians, so it is difficult to use it as a pass height warning system for the high height vehicles. In this paper, we propose a system that generates a warning by determining the correlation and time series characteristics of data for each segment using multiple lidar sensors and then determining the possibility of collision in the upper part of the vehicle. Also, the proposed system confirmed the proper operation through a real-time driving test and a system performance evaluation by the Korea Automobile Testing & Research Institute.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1874-1881
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• 2021

Black ice, which occurs mainly on the road, vehicle traffic bridges and tunnel entrances due to the sub-zero temperature due to the slip of the road due to heavy snow, is not recognized because the image of asphalt is transmitted in the driver's view, so the vehicle loses braking power because it causes serious loss of life and property. In this paper, we propose a method to identify the black ice by using infrared camera and to identify the road condition by using deep learning to compensate for the disadvantages of existing black ice detection methods (artificial satellite imaging, checking the pattern of slip by ultrasonic reception, measuring the temperature of the road surface, and checking the difference in friction force of the tire during vehicle driving) and to reduce the size of the sensor to detect black ice.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.111-116
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• 2022

The causes of motor burnout include overload, phase loss, restraint, interlayer short circuit, winding ground fault, instantaneous overvoltage, and the rotor contacting the stator, leading to insulation breakdown, leading to breakdown or electrical accidents. Therefore, equipment failure causes not only loss due to cost required for equipment maintenance/repair, but also huge economic loss due to productivity decrease due to process stop because the process itself including the motor is stopped. The current level of technology for diagnosing motor failures uses vibration, heat, and power analysis methods, but there is a limit to analyzing the problems only after a considerable amount of time has passed according to the failure. Therefore, in this paper, a device and algorithm for measuring insulation resistance using DC AMP signal was applied to an industrial motor to solve this problem. And by following the insulation resistance state value, we propose a diagnosis of deterioration and failure of the motor that cannot be solved by the existing method.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.35-43
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• 2023

Emotion recognition while driving is an essential task to prevent accidents. Furthermore, in the era of autonomous driving, automobiles are the subject of mobility, requiring more emotional communication with drivers, and the emotion recognition market is gradually spreading. Accordingly, in this research plan, the driver's emotions are classified into seven categories using psychological and behavioral data, which are relatively easy to collect. The latent vectors extracted through the auto-encoder model were also used as features in this classification model, confirming that this affected performance improvement. Furthermore, it also confirmed that the performance was improved when using the framework presented in this paper compared to when the existing EEG data were included. Finally, 81% of the driver's emotion classification accuracy and 80% of F1-Score were achieved only through psychological, personal information, and behavioral data.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.969-976
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• 2022

In this paper, a drunk driving prevention system was implemented to measure drunk driving before starting to prevent drunk driving accidents caused by complacency after drinking. In order to prevent a situation in which a driver but not a driver authenticates instead of a driver, the identification means was strengthened and the alcohol sensor was implemented to operate when the wind sensor measured above the set value set. Through this system, the driver's alcohol measurement process was strengthened. Sensors were determined through various experiments, and finally, when the alcohol concentration was 0.03% or more, the DC motor was stopped and the vehicle was designed to be unable to operate, thereby implementing a system in which drunk driving was prevented in advance.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.117-122
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• 2022

In this paper, we developed a vehicle control terminal using IoT and low-power long-distance communication (NB-IoT) technology. This system collects information on the location and status of a parked vehicle, and transmits the vehicle status to the vehicle owner's terminal in real time with low power to prevent vehicle theft, and in the case of a vehicle in motion, When primary information about the vehicle, such as an impact, is collected and transmitted to the server, the server analyzes the relevant data to generate secondary information on traffic congestion, road damage, and safety accidents. By sending it, you can know the exact arrival time of the vehicle at its destination. This terminal device is an IoT gateway for a vehicle and can be connected to various wired and wireless sensors inside the vehicle. In addition, the data collected from vehicle maintenance, efficient operation, and vehicles can be usefully used in the private or public sector.

• Korean Journal of Culture and Social Issue
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• v.17 no.4
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• pp.381-393
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• 2011

Eco driving is a strategy to reduce energy consumption and greenhouse gas emissions from motor vehicle. However, it has not received much attention until recently. Psychological studies on this issue have been limited and the majority of existing studies have primarily been based on engineering and educational approaches. This study examined the effects of a self-management technique on two driving behaviors: speeding and putting the gears in neutral while waiting at the signal. The self-management technique consisted of three behavior interventions: goal-setting, self-monitoring, and reward. Three drivers participated in this study. An AB multiple baseline design across participants was adopted. Results showed that the self-management technique was effective in increasing both driving behaviors. Implications of the present findings and suggestions for future research were discussed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.259-260
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• 2020

기존의 전동휠체어를 사용하는 약자 또는 중증 장애인 등 지체(肢體)가 불편한 사람들이 휠체어 사용 시 생기는 문제점을 해소할 목적으로 시작되었다. 이는 전동휠체어가 보행 기구임에도 자동차에 준하는 교통사고에 대해 무방비하게 노출되고, 중증 장애인에 대한 이동권 보장이 아직 미흡하여 생기는 문제이다. 따라서 본 연구에서는 이러한 문제로 인한 불편함을 해소하고자 아이트래킹을 이용한 스마트 전동휠체어 기술을 적용하고자 한다. 루게릭병 등으로 인해 지체(肢體)의 움직임에 제한이 있는 사람들에게 보호자가 밀어주는 휠체어에 의존하는 것이 아닌 Eye-Tracker를 이용한 시선 추적(Eye-Tracking) 기술로 휠체어 동작이 가능하다. Web-Cam과 라즈베리 파이를 통해 얻은 전·후·좌·우의 영상정보를 디스플레이 화면에 송출한다. 그 후 Eye-Tracking 기술을 이용해 디스플레이 화면에 표시된 전·후·좌·우 이동에 관한 UI(User Interface)룰 사용자가 송출된 영상을 보면서 눈의 움직임만으로 선택해 휠체어의 방향을 제어한다. 또한 전동휠체어의 조작 실수로 다른 행인 또는 장애물과 충돌하는 문제점을 초음파 센서를 이용하여 일정 거리 내에 사물이나 사람이 있을 경우 디스플레이 화면에 경고표시 및 경고음, 각 초음파 센서 위치에 맞는 LED작동으로 사용자들에게 추돌 위험경고와 함께 장애물의 위치파악이 가능하도록 한다. 따라서 스마트 전동휠체어를 통하여 수동적인 움직임이 아닌 능동적이고, 초음파 센서로 인해 안전한 이동이 가능하게 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.161-162
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• 2020

Major advanced ports around the world are preparing for environmental regulations such as increased efficiency of ports and low emission of pollutants in ports by utilizing fourth industrial technologies and ICT technologies such as AI, big data, self-driving cars and connected cars. It is also investing in developing fully unmanned terminals to solve the problem of workforce reduction caused by avoidance of 3D industries. However, the introduction of advanced technology is being delayed in domestic ports, which has led to a drop in port efficiency. In addition, port safety accidents have also occurred frequently, seriously affecting port marketing. Thus, the characteristics and types of each container terminal in Korea were analyzed and the factors for introducing autonomous cooperative driving were classified into five section factors and 15 division factors. Hierarchically classified factors will be surveyed on workers working in shipping lines, port construction, container terminals and related ministries.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.16-25
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• 2023

There are various types of foreign object debris (FOD) in the aviation industry. Tools lost by workers can act as a risk factor throughout aircraft operation, manufacturing, and maintenance fields. Accidents caused by tools lost due to workers' carelessness continue to occur throughout the aviation industry. Aviation-related institutions such as FAA and EASA have established tool control regulations and systems to prevent FOD occurrence. However, in Korea, related regulations and procedures are insufficient. A systematic and effective tool control system is required for reliable manufacturing, airworthiness, operation, and maintenance of aircraft. In this paper, tool control regulations and procedures of domestic and foreign air traffic authorities and aviation industry-related organizations were studied. A wireless communication-based tool control system was proposed based on the NAS 412's tool control regulations certified by the National Standards Association.