• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.132-145
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• 2022

This study was based on the black box images of traffic accidents on highways, cluster analysis and prediction model comparisons were carried out. As analysis data, vehicle driving behavior and road surface conditions that can grasp road and traffic conditions just before the accident were used as explanatory variables. Considering that traffic accident data is affected by many factors, cluster analysis reflecting data heterogeneity is used. Each cluster classified by cluster analysis was divided based on the ratio of the severity level of the accident, and then an accident prediction evaluation was performed. As a result of applying the Logit model, the accident prediction model showed excellent predictive ability when classifying groups by cluster analysis and predicting them rather than analyzing the entire data. It is judged that it is more effective to predict accidents by reflecting the characteristics of accidents by group and the severity of accidents. In addition, it was found that a collision accident during stopping such as a secondary accident and a side collision accident during lane change act as important driving behavior variables.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.334-338
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• 2012

현재 우리나라에서는 일반 자동차 부품처럼 보급되고 있는 자동차 블랙박스는 하드웨어 기반의 장비로, 추후 애로사항 수정 및 추가기능 업데이트가 불가능하다. 또한 여러 가지 물리적 문제로 인하여 많은 운전자들이 불편을 겪고 있다. 현재 출시된 블랙박스는 GPS와 영상정보만 수집하여 추후 저장된 사고기록을 바탕으로 사고원인의 규명 할 때 신뢰성이 낮은 결과가 나올 수 있다. 본 논문에서는 앞에서 서술한 기존 자동차 블랙박스의 문제점을 해결하고자 기존의 블랙박스에서 취급하는 정보 이외에 OBD프로토콜을 통해 수집되는 자동차 내부정보를 다루는 안드로이드 OS용 자동차 블랙박스 어플리케이션을 개발하고자 한다.

• Korean Journal of Crystallography
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• v.11 no.4
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• pp.231-237
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• 2000

CMR Materials RE/sub 1-x/Ca/sub x/MnO₃(RE=La, Nd, A=Ca, Sr) were grown using the floating zone image furnace with halogen lamps as heat source. The growth condition was at 2∼10 mm/hr growth rate in air atmosphere, were 445∼50 rpm and 20∼25 rpm of rotation rate of feedrod and growing crystal, respectively. The grown crystals showed shiny black color and annealed at 1500℃ in a box furnace to release the residual stress during cooling. Characterization analyses of the crystal were carried out using XRD and SEM. The crystal structure of Nd/sub 0.7/Ca/sub 0.3/MnO₃ was analyzed with smart CCD XRD was lattice parameter of a=5.425(4)Å, b=5.434(4)Å, and c=7.712(5)Å, an orthorombic system with space group of pbnm.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.538-540
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• 2015

안전 거리 미확보는 교통 사고 원인 중 3위에 이르는 큰 위험 요소이다. 이러한 차간거리 미확보로 인한 사고는 조금만 빨리 대응하여도 사전에 방지할 수 있다. 따라서 주행 중 실시간으로 차간 거리를 추정하여 제공하는 시스템이 필요하다. 본 논문에서는 안드로이드 기반의 실시간 촬영 영상에서 차량의 에지와 후미등을 이용하여 차량을 검출하고, 검출된 차량의 폭을 이용하여 차간 거리를 추정하여 제공하는 시스템을 제안하고, 구현 결과를 제시한다.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.34-38
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• 2020

In this paper, we implement a Dashcam system capable of shooting 360 degrees using a Raspberry Pi, shock sensors, distance sensors, and rotating camera with a servo motor. If there is an object approaching the vehicle by the distance sensor, the camera rotates to take a video. In the event of an external shock, videos and images are stored in the server to analyze the cause of the vehicle's accident and prevent the user from forging or tampering with videos or images. We also implement functions that transmit the message with the location and the intensity of the impact when the accident occurs and send the vehicle information to an insurance authority with by linking the system with a smart device. It is advantage that the authority analyzes the transmitted message and provides the accident handling information giving the user's safety and convenience.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.3-6
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• 2013

최근 차량용 블랙박스의 저장된 데이터의 안전성에 대한 관심도가 높아지고 있다. 현재의 차량용 블랙박스는 영상녹화 및 저장을 위해 보통 플래시 메모리를 삽입하여 사용하는데 이는 메모리의 분실 또는 데이터 파손 등 데이터 보관성에 문제를 일으킬 수 있다. 본 논문에서는 기존의 차량용 블랙박스의 데이터 안전성을 높이고자 클라우드 컴퓨팅 개념을 도입하여 사고발생 시 중요한 데이터를 서버에 최대한 업로드하고 이를 이용해 제 3자에게 영상 데이터를 제공하거나 사고를 통보 할 수 있는 기능을 가진 블랙박스 시스템을 안드로이드 OS에서 구현하고자 한다.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.76-80
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• 2018

In recent years, with the development of automobile technology, smart system technology that assists safe driving has been developed. A camera is installed on the front and rear of the vehicle as well as on the left and right sides to detect and warn of collision risks and hazards. Beyond the technology of simple black-box recording via cameras, we are developing intelligent systems that combine various computer vision technologies. However, most related studies have been developed to optimize performance in laboratory-like environments that do not take environmental factors such as weather into account. In this paper, we propose a method to detect object by restoring visibility in image with degraded image due to weather factors such as fog. First, the image quality degradation such as fog is detected in a single image, and the image quality is improved by restoring using an intermediate value filter. Then, we used an adaptive feature extraction method that removes unnecessary elements such as noise from the improved image and uses it to recognize objects with only the necessary features. In the proposed method, it is shown that more feature points are extracted than the feature points of the region of interest in the improved image.

• Smart Media Journal
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• v.9 no.3
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• pp.31-40
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• 2020

Currently, black-box-based machine learning algorithms are used to analyze big data in manufacturing. This algorithm has the advantage of having high analytical consistency, but has the disadvantage that it is difficult to interpret the analysis results. However, in the manufacturing industry, it is important to verify the basis of the results and the validity of deriving the analysis algorithms through analysis based on the manufacturing process principle. To overcome the limitation of explanatory power as a result of this machine learning algorithm, we propose a manufacturing big data analysis method using genetic programming. This algorithm is one of well-known evolutionary algorithms, which repeats evolutionary operators such as selection, crossover, mutation that mimic biological evolution to find the optimal solution. Then, the solution is expressed as a relationship between variables using mathematical symbols, and the solution with the highest explanatory power is finally selected. Through this, input and output variable relations are derived to formulate the results, so it is possible to interpret the intuitive manufacturing mechanism, and it is also possible to derive manufacturing principles that cannot be interpreted based on the relationship between variables represented by formulas. The proposed technique showed equal or superior performance as a result of comparing and analyzing performance with a typical machine learning algorithm. In the future, the possibility of using various manufacturing fields was verified through the technique.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1898-1905
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• 2012

This paper presents an On-board Smart Device (OSD) for moving vehicle, based on a smooth integration of Android-based devices and a Micro-control Unit (MCU). The MCU is used for the acquisition and transmission of various vehicle-borne data. The OSD has threefold functions: Record, Report and Alarm. Based on these RRA functions, the OSD is basically a safety and convenience oriented smart device, where it facilitates alert services such as accident report and rescue as well as alarm for the status of vehicle. In addition, voice activated interface is developed for the convenience of users. Vehicle data can also be uploaded to a remote server for further access and data manipulation. Therefore, unlike conventional blackboxes, the developed OSD lends itself to a user-friendly smart device for vehicle safety: It basically stores monitoring images in driving plus vehicle data collection. Also, it reports on accident and enables subsequent rescue operation. The developed OSD can thus be considered an essential safety smart device equipped with comprehensive wireless data service, image transfer and voice activated interface.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1792-1798
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• 2017

Event Data Recorder(Car Black-Box) with WiFi dongle have been released, and the platform of the majority is the Linux platform. This is because the platform development is possible in little investment cost by reducing the source licensing costs by taking advantage of the open source. But utilizing Linux platform has the limitations of boot-up time and consuming processing power due to the limitation of battery capacity, to be cost-competitive to minimize the use of memory. In this paper, the real-time operating system(RTOS) is utilized to optimize these portions. MP4 encoder and Muxer are developed to be about ten seconds boot up and minimized memory. It has the advantages of operating at lower power consumption than the Linux utilizing WiFi dongle. Utilizing a WiFi dongle is to provide a progressive download feature on smart phones to lower product prices. But RTOS has the weakness in WiFi. Porting TCP /IP, Web and DHCP server and combination with the USB OTG Host interface by implementing the protocol stack are developed for WiFi. And also SPI NOR flash memory is utilized for faster boot time and cost reductions, low processing power to be consume. As the results, the developed proved the 10 seconds booting time, 24 frame rate/sec. and 10% lower power consumption.