• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.05b
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• pp.102-105
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• 2005

가스센서는 응용 분야와 기능 및 종류가 다양하고 최첨단 분야로서 학문적으로는 물리, 화학, 전기, 전자 및 기계 등의 배경을 필요로 하며 산업적으로는 공업 전 분야와 농림, 축산, 사무기기에서 뿐만 아니라 공해 방진용(자동차 연소제어 및 배출가스 제어, 대기오염 감시등), 민생용(조리, 환기, 공조 등), 교통 보안용(음주운전측정 및 음주운전 방지장치 등), 방재용(가스 누설 탐지기, 불완전 연소 방지, 산소 결핍, 화재 등), 의료용(호기, 마취가스의 분석 등) 매우 광범위하며 점점 더 확대되어 가고 있다. 본 연구에서는 검출 가스 종류에 따라 졸-겔법으로 감응막을 최적 설계하고, 최적으로 설계된 감응막을 디핑법으로 코팅처리한 후 최적으로 열처리하여 센서를 제작하였다. 또한, 자체 제작한 가스검출 시스템에 제작된 센서를 장착하여 센서의 가스 검출 특성을 측정하고, 측정 데이터를 이용하여 휴대용 가스 검출 시스템을 설계 제작하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.561-571
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• 2014

This study analyzes traffic accident severity of old age drivers in fourteen cities and counties of Jeonbuk Province. It is assumed that traffic accident effecting factors have two staged structure by personal and driving environment and urban characteristics. Multilevel Analysis Model is used under the assumption of hierarchical characteristics to analyze factors effecting severity. As the driver's age increases after sixty-five years old, accident damages become severe. The drunk driving is likely to make traffic accident damage more severer. The number of fatal accident by old age drivers is about three time more than by no old age drivers. Old age drivers have higher number of night traffic accidents but severer ones in daytime. Old age drivers show the higher number of traffic accidents but severer ones in fine weather. Wet road surface also influences damage severity and especially old age drivers show higher serious damage and fatal than no old drivers.

• Korean Journal of Culture and Social Issue
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• v.15 no.3
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• pp.431-446
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• 2009

This study was intended to validate and develop the driving stress coping behavior scale. In a preliminary investigation, literature studies on the driving stress and open questionnaire were administered and examined in four regions in Korea. As a result, 64 items driving stress questionnaire were developed. In the study, this Driving Stress Coping Behavior Scale(DS-CBS) was examined to 372 drivers located seven regions in Korea. The factors analysis revealed 2 meaningful factors[(Good Coping: GC), (Bad Coping: BC) with 24 items. When internal consistency for each 2 factor was calculated, all sub-scale revealed a satisfactory level of Cronbach's α. Also, correlations with Driver Coping Questionnaire(DCQ) and risk driving behaviors(speed driving, drunken driving, traffic violation, offence accident, defence accident) supported consistently validity of the Driving Stress Coping Behavior Scale(DS-CBS). Also, We investigated the influences of 'Good Coping', 'Bad Coping' consisting of driving stress coping behavior, on traffic accidents risk. As a result, 'Good Coping' and 'Bad Coping' influenced traffic accidents risk. 'Good Coping' had decreased effects, the other side 'Bad Coping' had increased effects on traffic accidents risk(TARI).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.540-546
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• 2023

The scope of IoT use has expanded due to the development of related technologies, and various sensors have been developed and distributed to meet the demand for implementing various services. Measuring alcohol concentration using a sensor can be used to prevent drunk driving, and to make this possible, accurate alcohol concentration must be measured and safe transmission from the smartphone to the server must be guaranteed. Additionally, a process of converting the measured alcohol concentration value into a standard value for determining the level of drinking is necessary. In this paper, we propose and implement a system. Security with remote servers applies SSL at the network layer to ensure data integrity and confidentiality, and the server encrypts the received information and stores it in the database to provide additional security. As a result of analyzing the accuracy of alcohol concentration measurement and communication efficiency, it was confirmed that the measurement and transmission were within the error tolerance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.947-950
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• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.768-773
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• 2012

One of the main reasons for serious road accidents is driving while drowsy. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. One of the effective signals is to measure electroencephalogram (EEG) signals and electrooculogram (EOG) signals. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, drowsiness, sleepiness. This paper proposes a drowsiness detection system using Linear Predictive Coding (LPC) coefficients and Support Vector Machine (SVM). Samples of EEG data from each predefined state were used to train the SVM program by using the proposed feature extraction algorithms. The trained SVM program was tested on unclassified EEG data and subsequently reviewed according to manual classification. The classification rate of the proposed system is over 96.5% for only very small number of samples (250ms, 64 samples). Therefore, it can be applied to real driving incident situation that can occur for a split second.

• Analytical Science and Technology
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• v.33 no.3
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• pp.151-158
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• 2020

Alcohol, which can easily be obtained in the same way as ordinary beverages, is harmful enough to cause death due to excessive drinking and chronic alcohol intake, so it is important to maintain a proper amount of drinking and healthy drinking habits. In addition, the incidence of behavioral disturbances and impaired judgments that can be caused by chronic alcohol drinking of more than adequate amounts of alcohol is also significant. Accordingly it is very useful for forensic science to check whether the person involved is drunken or is alcoholism state in various accidents. Currently, in Korea, alcohol consumption is determined by detecting the level of alcohol or alcohol metabolism 'ethyl glucuronide (EtG)' in blood or urine samples. However, analysis of alcohol or EtG in blood or urine can only provide information about the current state of alcohol consumption because of a narrow window of detection time. Therefore, it is important to analyze the EtG as a long-term direct alcohol metabolite bio-marker in human hair and to investigate relationship between alcohol consumption and EtG concentration for the evaluation of chronic ethanol consumption. In this study, we established an analytical method for the detection of EtG in Korean hair efficiently and validated selectivity, linearity, limits of detection (LOD), limits of quantification (LOQ), matrix effect, recovery, process efficiency, accuracy and precision using liquid chromatography tandem mass spectrometry (LC-MS/MS). In addition, the assay performance was evaluated in Korean social drinker's hair and the postmortem hair of a chronic alcoholism. The results of this study can be useful in monitoring the alcohol abuse of Korean in clinical cases and legal procedures related to custody and provide a useful tool to evaluate postmortem diagnosis of alcoholic ketoacidosis in forensics.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.109-117
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• 2005

Based on the previous studies on alcohol effects on human behavior and performance in transportation system such as airplane and car driving, the alcohol exposure before and on watch of a ship has a great influence on subsequent behavior. In this paper, to examine the drinking status of officers on board multiple choice questionnaires are circularized under instruction and surveyed for 118 officers. According to the results of the questionnaire survey on alcohol dependance (Alcoholism) that was invested by WHO, over 27% of those surveyed represented alcohol abuse symptoms. In addition to that, the existing state and awareness for on-board-drinking was summarized to make a scenario of drunk-operation with a ship handling simulator to investigate the effect of alcohol (0.08 g% blood alcohol concentrations) on ship operational performance. A main effect for alcohol was found indicating that ship operational performance was comparatively impaired by this alcohol relative to performance in the non-alcohol condition. The results of this research can be applied to minimize marine acciedents as basic data.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.136-141
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• 2012

One of the main reasons for serious road accidents is driving while drowsy. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. One of the effective signals is to measure electroencephalogram (EEG) signals and electrooculogram (EOG) signals. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, drowsiness, sleepiness. This paper proposes a neural-network-based drowsiness detection system using Linear Predictive Coding (LPC) coefficients as feature vectors and Multi-Layer Perceptron (MLP) as a classifier. Samples of EEG data from each predefined state were used to train the MLP program by using the proposed feature extraction algorithms. The trained MLP program was tested on unclassified EEG data and subsequently reviewed according to manual classification. The classification rate of the proposed system is over 96.5% for only very small number of samples (250ms, 64 samples). Therefore, it can be applied to real driving incident situation that can occur for a split second.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.643-656
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• 2019

The development of hot social networking services, including the Internet, has transformed rental car services into IT-based car-sharing services. The car-sharing service is a service that allows people to rent cars online without having to face-to-face. It has become the preffered service among young people who are accustomed to drinking and eating alone. Users can use their smartphones to book their types of cars and hours of rent, and then go to a nearby designated parking lot to use their reserved cars. You can open a designated car door with a smart phone and drive. It is a very convenient service to pay for the distance you drive. However, the car-sharing service already in use in business has the following problems: underage who do not have a driver's license may drive a car borrowed by an acquaintance, the status of a license registered at the time of join membership with a car-sharing company may change to a suspension or cancellation of a license while renting and driving, or even a drunk person may rent a car and drive. In this paper, the method to solve these problems has been studied and proposed. The proposed method is to reduce the cost of investment by a car-sharing service provider and to minimize user inconvenience. And, it was compared and analyzed with the existing method. For the method to be used efficiently, the active operation of the car-sharing company and the government's policies will have to be supported.