• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.1000-1003
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• 2013

The monitoring system using a surveillance camera, has the advantage that can be observed in real time the blind spot of the crime, case to be mounted is increasing. However, surveillance camera, is used for the purpose of verification of the crime later than risk detection of crime before advance. Therefore, in this paper, in order to supplement the weak information collection monitoring system using the monitoring camera, by using the position information of the smartphone, infers the person monitoring region, the movement path of the image information other event occurs it is a fusion iT monitoring system that provides information of the user who judged. Result of the experiment, the proposed system confirmed the improved efficiency and usability than conventional systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1071-1074
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• 2021

본 논문은 펌웨어와 인공지능을 이용하여 지형의 사각지대를 이동하며 순찰 및 방범의 목적을 지닌 시스템을 소개하기 위함에 있다. 기존의 보안 시스템은 비상 상황 발생 시 인력이 직접 출동하여 상황을 해결함으로써 날로 증가하는 최저임금을 고려했을 때 이들의 인건비를 감당하기 어렵다는 단점이 있다. [1] 이러한 문제점을 해결하기 위해 앱 개발을 통해 RC카를 제어하는 아두이노와 연결하여 자율주행을 하게끔 하는 시스템을 개발했다. 또한, 라즈베리파이 웹캠을 부착해 실시간으로 현장을 촬영하여 사용자가 웹에만 접속하면 현장을 모두 감시할 수 있도록 시스템을 개발하였고, 단시간 푸리에 변환(STFT)을 통해 얻은 음성 데이터 변환맵을 인공지능 프로세서인 인텔리노에 학습 데이터로 학습시킨 후에 주변 환경에서 비명 소리만 감지할 수 있도록 시스템을 구현하였다. 본 논문에서는 이러한 시스템들이 기존의 인건비 증가에 대한 문제점을 해소할 수 있다고 생각하여 더욱 효율적으로 방범이 가능한 시스템을 소개한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.131-136
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• 2016

In this paper, we propose an Raspberry Pi2-based smart home security monitoring system. Proposed home security monitoring system was configured using a relatively tractable main processor raspberry pi2, ultrasonic sensors, and PIR sensors. In addition, The picamera is compatible with raspberry pi2 was connected to the servo motor. And by driving the attacker's location the video was recording. The Web server stores data of the recorded image and the sensor, and provides a web page to enable the monitoring at all remote locations. When examining efficiency of proposed home security monitoring system it was found that proposed system is easier to be made than existing home security system and is able to minimize the blind spot of the camera by using servo motor and is efficient and convenient and stable as it enables a user to handle an error in person and it uses reliable data.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.147-155
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• 2024

Purpose: The purpose of this study is to analyze the danger signs of buildings and present a plan to install a building monitoring system to develop measurement technology for small private buildings in the blind spot of disaster safety. Method: The cause of building risk behavior, components of monitoring measuring equipment, location of measuring equipment installation, management plan, etc. are presented. Result: Measuring instruments essentially include acceleration sensors, tilt sensors, gyro sensors, GPS, etc. The measuring instrument should take into account the height and cross-sectional area of the pillar. Conclusion: The results of this study can strengthen disaster safety capabilities in preparation for disasters arising from building collapses that may occur in small private buildings.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.3
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• pp.233-241
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• 2014

This paper contributes to development of a new method for detecting rear-side vehicles and estimating the positions for blind spot region or providing the lane change information by using vision systems. Because the real image acquired during car driving has a lot of information including the target vehicle and background image as well as the noises such as lighting and shading, it is hard to extract only the target vehicle against the background image with satisfied robustness. In this paper, the target vehicle has been detected by repetitive image processing such as sobel and morphological operations and a Kalman filter has been also designed to cancel the background image and prevent the misreading of the target image. The proposed method can get faster image processing and more robustness rather than the previous researches. Various experiments were performed on the highway driving situations to evaluate the performance of the proposed algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.429-440
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• 2010

It is known that as many as 1 in 91 children are diagnosed with an autistic spectrum disorder, and the incidence rate of the autistic spectrum disorder is much higher than that of cancer in Korea. It is necessary to develop a novel technology to sense their emotional status and give proper psychological diagnosis and therapy, since the children with autistic spectrum disorder usually do not express their own emotional status. This article presents the state-of-the-arts on the affective computing technologies that include recognition of emotional status through bio-sensing and virtual affective agent modeling, and then proposes a novel system architecture for diagnosis and therapy of autistic spectrum disorder. The diagnosis and therapy system of autistic spectrum disorder is composed of bio-sensing module, virtual environment module with affective agents, and haptic interface module. The architecture proposed in this paper will enhance the objectivity to diagnose autism spectrum disorders, and enable continuous treatment in daily life.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.224-226
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• 2016

With the technical development and rapid increase of private demand, the new market for unmanned vehicle combined with the characteristics of 'unmanned automation' and 'vehicle' is rapidly growing. Even though the pilot driving is currently allowed in some countries, there is no country that has institutionalized the formal driving of self-driving cars. In case of the existing vehicles, safety incidents are frequently happening due to the frequent malfunction of the rear sensor, blind spot of the rear camera, or drivers' carelessness. Once such minor flaws are complemented, the relevant regulations for the commercialization of self-driving car and small drone could be relieved. Contrary to the ultrasonic and laser sensors used for the existing vehicles, this paper aims to attempt the distance measurement by using the depth sensor. A depth camera calculates the distance data based on the TOF method calculating the time difference by lighting laser or infrared light onto an object or area and then receiving the beam coming back. As this camera can obtain the depth data in the pixel unit of CCD camera, it can be used for collecting depth data in real-time. This paper suggests to solve problems mentioned above by using depth data in real-time and also to design the obstacle avoidance system through distance measurement.