• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.605-611
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• 2023

Accidents at construction sites have a very high rate of fatalities due to the nature of being prone to severe injury patients. In order to reduce the mortality rate of severely injury patients, quick response is required, and some systems that detect accidents using AI technology and cameras have been devised to respond quickly to accidents. However, since existing accident detection systems use only a single camera, there are blind spots, Thus, they cannot detect all accidents at a construction site. Therefore, in this paper, we present the system that minimizes the detection blind spot by using multiple cameras. Our implemented system extracts feature points from the images of multiple cameras with the YOLO-pose library, and inputs the extracted feature points to a Long Short Term Memory-based recurrent neural network in order to detect accidents. In our experimental result, we confirme that the proposed system shows high accuracy while minimizing detection blind spots by using multiple cameras.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.315-328
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• 2024

Purpose: The purpose of this paper is to present a service construction plan using multiple complex sensor information to detect abnormal situations in urban life safety that are difficult to identify on CCTV. Method: This study selected service scenarios based on actual testbed data and analyzed service importance for local government control center operators, which are main users. Result: Service scenarios were selected as detection of day and night dynamic object, Detection of sudden temperature changes, and Detection of time-series temperature changes. As a result of AHP analysis, walking and mobility collision risk situation services and fire foreshadowing detection services leading to immediate major disasters were highly evaluated. Conclusion: This study is significant in proposing a plan to build an anomaly detection service that can be used in local governments based on real data. This study is significant in proposing a plan to build an anomaly detection service that can be used by local governments based on testbed data.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.8-14
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• 2014

In this paper, we propose a new fire detection method using moving features and colors of flames in video sequences. It uses YCbCr color space to separate the luminance from the chrominance components more effectively than RGB color space. In the proposed method, moving regions of flames are detected by cumulating the difference of luminance between two consecutive images and generate candidate flame regions by using the color of flames. Finally, it decides whether the candidate flame regions are flames or not by using their temporal changes of the areas. Experimental results show that the proposed method performs better in segmenting fire regions compared with the conventional fire detection method in video sequences.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.95-102
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• 2016

Pipeline is making the most use of transportation of petroleum products on the land. But due to tremendous accident or environmental disaster by oil pipeline leak or pipeline stolen, leak detection systems have been used for preventing it. Leak detection method based on negative pressure wave has been used at the long distance pipeline. But even if it has showed good leak detection quality, due to making a lot of false alarm, it has weak point that disturbs concentration to system. This study suggests algorithm and method of using volume balance to decrease false-alarm of pipeline leak detection system based on negative pressure wave.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.4
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• pp.403-406
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• 2016

This paper presents the design and implementation of the small size receiver to put a passive microwave sensor for human body detection to practical use. The requirements and specifications of the sensor receiver are drawn using the experimental data of human body detection by the existing sensor operated at 5.1 GHz. The small size sensor receiver to satisfy the drawn specifications is designed and implemented. The effectiveness of the fabricated sensor with small size receiver on human body detection is demonstrated experimentally in laboratory. The results show the sensor can detect human body to within 4 m distance from the antenna. The size and power consumption of the small size receiver are decreased to 60 % and 40 % compared to those of the existing receiver, respectively.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.601-604
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• 2021

본 논문에서는 모바일 디바이스의 카메라로부터 얻은 RGB이미지를 분석하여 장애물을 안정적으로 탐지할 수 있는 프레임워크를 제안한다. 본 논문에서는 장애물을 안정적으로 찾기 위해 RANSAC(Random Sample Consensus)기반의 다중 평면 방식을 이용한 위험감지 시스템을 제안한다. 우리의 접근 방식은 RGB영상으로부터 특징점(Feature point)을 추출하고, 특징점을 분석(Feature point analysis)하여 영상내의 평면을 감지한다. 복잡한 지형으로 인해 생성되는 다수의 평면을 RANSAC을 통해 단일 평면으로 정규화하고, 이로부터 특징점을 분류하기 위한 기준점을 계산한다. 모바일 디바이스의 위치와 회전 제약 없이 효과적으로 기준평면(Reference plane)을 탐색할 수 있고, 영상 내 특징점을 실시간으로 계산한다. 다양한 실험을 통해 기준평면과 장애물과의 거리를 파악하여 장애물을 효과적으로 분류하는 결과를 얻었다. 우리의 기법은 실세계에서의 위험요소를 감지하고 모바일 디바이스 사용자의 안전성 확보에 활용할 수 있을 거라 기대한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.28-30
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• 2021

In this paper, an algorithm that detects the user's finger direction using the YOLO (You Only Look Once) library was proposed. The processing stage of the proposed finger direction detection algorithm consists of a learning data management stage, a data learning stage, and a finger direction detection stage. As a result of the experiment, it was found that the distance between the camera and the finger had a very large influence on the accuracy of detecting the direction of the finger. We plan to apply this function to Turtlebot3 after improving the accuracy and reliability of the proposed algorithm in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1237-1242
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• 2017

Computer vision is coming more interesting with new imaging sensors' new capabilities which enable it to understand more its surrounding environment by imitating human vision system with artificial intelligence techniques. In this paper, we made experiments with Kinect camera, a new depth sensor for object detection and distance measurement functions, most essential functions in computer vision such as for unmanned or manned vehicles, robots, drones, etc. Therefore, Kinect camera is used here to estimate the position or the location of objects in its field of view and measure the distance from them to its depth sensor in an accuracy way by checking whether that the detected object is real object or not to reduce processing time ignoring pixels which are not part of real object. Tests showed promising results with such low-cost range sensor, Kinect camera which can be used for object detection and distance measurement which are fundamental functions in computer vision applications for further processing.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.10
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• pp.100-106
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• 2009

In this study, methods of overheat detection at the coupling or wire in electrical facility are investigated, operating characteristic about the optic temperature sensor for continuous on-line temperature monitoring in diagnostics system of electrical facility is analyzed. Heating sources in the experiment for operating characteristics of optic temperature sensor use black body and hot plate, output voltage of optic temperature sensor in accordance with temperature variation is analyzed. Overheat generation due to poor contact at the circuit breaker in panel board detects using a thermocouple, infrared thermal camera and optic temperature sensor, and experiment results are analyzed. The effect of optic temperature sensor is the same that of other methods. These results expect to use basic research material for adjusting field of electrical diagnostics system using RFID type optic temperature sensor in the near future.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.376.2-376.2
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• 2014

마이크로볼로미터 적외선 센서는 인체감지, 전자부품의 품질검사, 에너지 절감, 산업시설감시 및 군사용으로 다양하게 적용되고 있다. 기존에 이러한 적외선 센서의 감지재료로 VOx 또는 비정질 Si이 가장 많이 사용되고 있으며, VOx는 감도가 높고, 세계적으로 가장 많이 사용되고 있는 물질이다. 본 연구에서는 기존의 VOx 박막 증착법을 개선하여 Zn 산화물 박막을 혼용한 적외선 감지재료를 이용한 마이크로볼로미터 제작 및 특성에 대해 보고한다. RF sputtering 방법으로 약 140 nm의 VOx/ZnO/VOx 샌드위치 박막을 증착하고, 산소분위기에서 열처리함으로써 온도저항계수(TCR)가 약 -3.0 %/K의 값을 갖는 특성을 구현하였다. 갓 증착된 V-Zn 박막에서는 XRD 스펙트럼에서는 V2O5 관련 피크가 주로 관측되었으며, 산소열처리에 의해 VO2 피크가 새롭게 관측되었다. 볼로미터 감지소자는 유효면적 $50{\times}50{\mu}m^2$ 으로 bulk micromaching 공정을 통해 제작하였다. Si 기판위에 SiNx 박막을 PECVD 장치를 이용하여 증착하였으며, 적외선 감지층으로 V-Zn 산화물을 RF sputtering 방법으로 증착하여 열처리 후 SiNx passivation 박막으로 보호하였다. 열적고립을 위해 패터닝 후 Si 기판을 KOH 용액을 이용하여 약 $20{\mu}m$ 식각하여 소자를 구현하였다. 제작된 소자의 특성을 평가한 결과 반응도는 1.57e+4 V/W, 탐지도는 $8.79e+7cmHz^{1/2}/W$를 얻을 수 있었다. 소자의 동작 특성을 평가하기 위해 진공 압력을 1e-3 torr 이하에서 thermoelectric cooler를 장착한 metal package를 제작하여 동작온도에 따른 특성을 평가하였다. 동작온도를 $10^{\circ}C{\sim}40^{\circ}C$로 하여 측정한 결과 동작온도가 증가할수록 신호전압은 감소함을 알 수 있었다.