• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.107-108
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• 2016

Our study proposes the methods of distinguishing vehicle types using the interval and size of the car. The car videos converts the basic RGB model to Gray model for use and through Canny Edge Direction, it eliminates the background of the car while obtaining feature points through the detection of contours.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.705-710
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• 2003

Recent years, as a rapid development of multimedia technology, video database system to retrieve video data efficiently seems to core technology in the oriented society. This thesis describes an efficient automatic frame detection and location method for content based retrieval of video. Frame extraction part is consist of incoming / outgoing car frame extraction and car number frame extraction stage. We gain star/end time of car video also car number frames. Frames are selected at fixed time interval from video and key frames are selected by color scale histogram and edge operation method. Car frame recognized can be searched by content based retrieval method.

• Korean Journal of Veterinary Service
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• v.41 no.4
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• pp.245-250
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• 2018

Lawsonia intracellularis is the pathogenic agent of porcine proliferative enteritis (PPE). The bacterial pathogen infects the intestinal crypt cells which causes hyperplasia of the infected cells and leads to the process of intestinal pathogenesis. PPE includes some clinical maninfestations, including acute hemorrhagic diarrhea with sudden death in growing pigs and porcine intestinal adenomatosis, to a chronic diarrhea with reduced productivity of the infected pigs. The purpose of the present studies were carried out to determine L. intracellularis in livestock transport car of slaughterhouse. Distribution of L. intracellularis in livestock transport car were conducted using real-time polymerase chain reaction (real-time PCR) testing method, total 300 samples. Of 300 samples, 119 (39.7%) were detected as positive to L. intracellularis in livestock transport car. In seasonal analysis, 42 (28.0%) out of 150 samples in spring and summer season. 77 (51.3%) out of 150 sample in autumn and winter season. In regional analysis, 53 (88.3%) out of 60 cars and the detection ratio showed that regional variation in livestock transport car.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.201-209
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• 2015

The deformed degree of car body varies largely with the collision part from side collision of car-to-car. In case of deformation of car body caused by collision, the movement is different as speed energy changes to strain energy. Generally, in the analysis of traffic accident, the movement of car after the collision is analyzed by law of conservation of motion and the error of energy absorption rate along the deformation of car body can be calibrated by inputting coefficient of restitution, but it is current situation that coefficient of restitution applied by referring to the research results of forward collision and backward collision because the research results of side collision is rare. Vehicle model of finite element method applied by structure of car body and materials of each component was analyzed by explicit finite element method, and coefficient of restitution and collision detection time along contact part of side collision was drawn by analyzing the results. Analysis result acquired through the law of conservation momentum by applying finally-computed coefficient of restitution and crash detection time compared to collision result of actual vehicle. As a result, the reliability of analysis was higher than the existing analysis method were acquired when applying the drawn initial input value that used finite element method analysis model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.5
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• pp.812-816
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• 2015

Recently, various monitoring systems have been proposed to detect interaction performance between trains and infrastructure, as well as, various techniques to improve the accuracy and performance of such inspection equipment in high speeds. Especially, it is important to predict electric noise of high speed trains due to its effect on detection system accuracy. In this paper, we analyze various types of electrical noise in electric vehicles to improve the accuracy of the detection module of the inspection car. In detail, analysis of electric noise of high speed railway is performed as a function of speed based on field tests that were carried out by HEMU-430X (Highspeed Eletric Multiple Unit - 430 km/h eXperiment).

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.161-166
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• 2021

The term parking management system usually refers to the custom built hardware intensive systems installed in building and malls. However, there are many places where such expensive solutions cannot be installed due to various reasons, like cost and urgent/temporary setup requirements. This project focuses on developing a parking management system based on image processing to detect vacant parking slot in an area where automated systems are not installed. Camera images of the parking area are subjected to image processing algorithm which marks virtual slots in the area and extracts occupancy information to guide the incoming drivers about availability and position of vacant spaces. The application consists of two interfaces: one for the guidance of the incoming drivers and the other one for the administrator. The later interface also informs the administrator if a car is not parked properly in the virtual slot. This parking system would reduce the stress and time wastage associated with car parking and would make the management of such areas less costly.

• Smart Media Journal
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• v.13 no.1
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• pp.24-35
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• 2024

The combination of Artificial Intelligence and the Internet of Things (AIoT) has gained significant popularity. Deep neural networks (DNNs) have demonstrated remarkable success in various applications. However, deploying complex AI models on embedded boards can pose challenges due to computational limitations and model complexity. This paper presents an AIoT-based system for smart parking lots using edge devices. Our approach involves developing a detection model and a decision tree for occupancy status classification. Specifically, we utilize YOLOv5 for car license plate (LP) detection by verifying the position of the license plate within the parking space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.481-484
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• 2011

Recent Automotive technology is driven from mechanical device to the electronic components which improve the vehicle's safety and convenience. The future competitiveness of the car will come from safety issues and energy efficiency, convenience and the application of the technologies. In this study, various techniques for driver drowsiness detection are introduced and compared with each others. The advantages and disadvantages of commercially available technologies and developed technologies are compared. To enhance the detection resolution, multiple sensing technologies are introduced in this paper. The feasibility of two drowsiness detection methods, that is, existing camera image recognition method and bio signal analysis method, are tested. The direct drowsiness detection by the camera image of eyes and driver's vital signs detected indirectly are combined and analyzed by the developed noble algorithm for stress, fatigue, drowsiness detection with a more accurate high-drowsiness detection.

• Journal of Sensor Science and Technology
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• v.26 no.6
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• pp.432-437
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• 2017

As 4.0 industry has been developed, research on a self-driving car technology and related parts of an automobile has been highly investigated recently. Particularly, a TAS(Torque Angle Sensor) module on steering wheel system has been considered as a key technology because of its precise angle, torque detection and high speed signal processing. The environmental assessment is generally required on the TAS module to examine high resolution of angle/torque detection. In the case of existing TAS module, angle detection errors has been occurred by back-lash on main and sub gear in addition to complicated structure caused by gears. In this paper, a structure of the TAS module, which minimizes the numbers of components and angle detection errors on the module compared with the existing TAS module, for vehicle steering system based on a Multi-track Encoder has been proposed. Also, angle detection signal processing board, and key technology of the TAS module were fabricated and evaluated. As a result of the experiments, we confirmed an excellent performance of the fabricated signal processing board for angle detection and an applicability of the fabricated angle detection board on the TAS module of vehicles by the environmental assessment an automobile standard.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1234-1239
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• 2006

신속하고 정확한 교통정보 서비스의 제공은 원활한 교통소통을 위하여 필수적인 요소이다. 특히, 교통사고, 도로보수 그리고 자연재해와 같은 유고가 발생할 경우, 운전자에게 즉시 통보해주어 우회할 수 있도록 조치하는 것이 필요하다. 이를 위하여 다양한 교통정보 수집기에서 수집된 교통정보를 바탕으로 실시간으로 유고상황을 판별하는 연구가 많이 진행되고 있다. 유고상황 분석은 다양한 환경요인으로 인해 판별이 어렵고, 최근에 활용되고 있는 인공지능 기법은 검지에 드는 시간 비용이 많다는 문제를 가지고 있다. 본 연구에서는 과거에 발생한 각종 돌발 상황을 분석하여 실시간으로 유고상황을 검지하는 것이 목적이다. 유고검지를 위해 GPS를 탑재한 probe car에서 수집된 차량속도와 온라인으로 제보된 유고정보를 ANFIS를 이용하여 분석 후 유고상태를 판별한다. 본 연구를 통해 실시간 도로 이용자들이 유고 발생 지역의 정보를 제공받고 그 상황에 신속하게 대처하게 함으로써 교통 혼잡 완화에 기여할 것으로 기대한다.