• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.1-6
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• 2019

CCTV video recording system is recognized as evidence value of video data, and is widely used in real life for the purpose of security of facilities or security control, and it is developing in order to process high-resolution and high-capacity data in real time through network. However, there is no description of redundancy to prevent the loss of image data due to defects of unexpected equipment or external attack, and even if the redundancy is implemented, a high-capacity video stream is transmitted through the network, network overload can not avoided. In this paper, we propose and verify a failover method based on rules that can operate the redundancy scheme without inducing network overload in CCTV network video recording environment.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.397-408
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• 2021

The construction industry has the highest occupational accidents/injuries and has experienced the most fatalities among entire industries. Korean government installed surveillance camera systems at construction sites to reduce occupational accident rates. Construction safety managers are monitoring potential hazards at the sites through surveillance system; however, the human capability of monitoring surveillance system with their own eyes has critical issues. A long-time monitoring surveillance system causes high physical fatigue and has limitations in grasping all accidents in real-time. Therefore, this study aims to build a deep learning-based safety monitoring system that can obtain information on the recognition, location, identification of workers and heavy equipment in the construction sites by applying multiple object tracking with instance segmentation. To evaluate the system's performance, we utilized the Microsoft common objects in context and the multiple object tracking challenge metrics. These results prove that it is optimal for efficiently automating monitoring surveillance system task at construction sites.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.268-271
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• 2013

CCTV는 사람들 생활에서 없어서는 안 되는 유용한 존재로 자리매김 했다. 가장 큰 장점은 범죄 수사과정에서 유전자나 지문감식에 견줄 만큼 기여도가 크다는 점이다. 폭력 및 범죄를 해결하는데 유용하게 쓰이고 있고 날로 발전하고 있는 상황이다. 본 연구에서는 최근 공간정보기술의 발달에 따라 여러 분야에 공간 정보 기반의 관제시스템이 운영 중이거나 추진 중에 있으며, 지능형 영상감시를 위한 동향과 CCTV 설치에 따른 합법성과 프라이버시 보호에 대해 연구를 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.840-841
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• 2023

본 논문에서는 치안 공백 문제 해결을 위해 인공지능 CCTV를 소개한다. 자율주행 RC카의 센서 및 영상 처리로 행인의 이상 행동을 자동 탐지하고 이를 통합 관제 애플리케이션과 웹사이트로 확인 및 제어하는 시스템을 개발하였다. 이 시스템은 부족한 인력을 지원하고 CCTV 사각지대를 최소화하며, 이를 통해 공공 안전에 이바지함으로써 시민들이 안전하게 살 수 있는 사회가 구축되기를 기대한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.400-402
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• 2019

The electric point machine, which is used for the control of the turnout used to change the track of the train, is very important in the railway system. Various wired and wireless real-time monitoring systems are used to check the status of the point machine, but there is a possibility of malfunction due to sensor or network error. In this paper, a redundant monitoring system was designed that incorporates the point machine monitoring system and the CCTV camera control system to double check the operation of the point machine. In the point machine monitoring system, the operating state of the railway converter is monitored, alarmed and transmitted over the network. The CCTV camera control system, which received this information, was required to record the status of the turnout and the point machine in question and send it to the administrator. The manager of the railway line can check the conversion status of the railway through the monitoring screen for the railway line switcher first, and then confirm the switching status directly through the CCTV camera image, thereby improving the reliability of the point machine operation. It will also enable the safe and efficient operation of personnel for management. It is expected to contribute to preventing a derailment caused by a malfunction of the point machine.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.225-227
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• 2022

Now In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office in Seoul has built a control center for CCTV control and is building information such as people, vehicle types, license plate recognition and color classification into big data through 24-hour artificial intelligence intelligent image analysis. Seoul Metropolitan Government has signed MOUs with the Ministry of Land, Infrastructure and Transport, the National Police Agency, the Fire Service, the Ministry of Justice, and the military base to enable rapid response to emergency/emergency situations. In other words, we are building a smart city that is safe and can prevent disasters by providing CCTV images of each ward office. In this paper, the CCTV image is designed to extract the characteristics of the vehicle and personnel when an incident occurs through artificial intelligence, and based on this, predict the escape route and enable continuous tracking. It is designed so that the AI automatically selects and displays the CCTV image of the route. It is designed to expand the smart city integration platform by providing image information and extracted information to the adjacent ward office when the escape route of a person or vehicle related to an incident is expected to an area other than the relevant jurisdiction. This paper will contribute as basic data to the development of smart city integrated platform research.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.141-149
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• 2022

In this paper, we propose a design of CCTV enlcosure record management system based on blockchain. Since CCTV video records are transferred to the control center through enclosure, it is very important to manage the enclosure to prevent modulation and damage of the video records. Recently, a smart enclosure monitoring system with real-time remote monitoring and opening and closing state management functions is used to manage CCTV enclosures, but there is a limitation to securing the safety of CCTV video records. The proposed system detect modulated record and recover the record through hash value comparison by distributed stored record in the blockchain. In addition, the integrity verification API is provided to ensure the integrity of enclosure record received by the management server. In order to verify the effectiveness of the system, the integrity verification accuracy and elapsed time were measured through experiments. As a result, the integrity of enclosure record (accuracy: 100%) was confirmed, and it was confirmed that the elapsed time for verification (average: 73 ms) did not affect monitoring.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1583-1588
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• 2013

According to 2008 statistics, there is a need for sailing lookout to minimize the ships collision that caused a secondary damage such as environment pollution and it happened 25 percentage rate. The aim of this study is to construct the object targeting system for notifying the sailing and ship information as monitoring the marine with CCTV having a zoom, rotation, and tile function. In this study we expected to induce the safety sailing by offering the CCTV automatic treatment.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.736-738
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• 2018

최근 딥러닝의 발전에 따라 무인감시, CCTV 등 영상감시 시스템도 지능화되고 있다. 하지만 쓰레기 무단투기 감시는 여전히 관리자가 실시간으로 CCTV 영상을 관제하는 형태로 이루어지고 있다. 이러한 문제를 해결하기 위해 본 논문에서는 CCTV 영상에서 쓰레기 무단투기를 검출하는 방법을 제안하며 검출 방법으로 차 영상과 합성곱 신경망을 이용한다. 실험은 합성곱 신경망에서의 쓰레기봉투 분류 문제 위주로 진행하였다. 합성곱 신경망의 네트워크는 Inception v3를 사용하였으며 실험 결과, 약 99.52%의 쓰레기봉투 분류율을 얻을 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.425-426
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• 2022

Many CCTVs are installed around the area for the purpose of preventing crime. In this case, it is necessary to sound an alarm when a specific situation occurs because many people cannot be watching CCTV. It is necessary to analyze the video data to determine what kind of behavior it is. In this study, we propose a scene change detection technique through histogram operation, paying attention to the change of the histogram due to a sudden movement.