• Title/Summary/Keyword: AI CCTV

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Development of CCTV for Identification of Maskless Wearers based on Deep Learning (딥러닝 기반 마스크 미착용자 식별 CCTV 개발)

  • Lee, Se-Hoon;Kwon, Hyeon-guen;Kim, Young-Jin;Jeong, Ji-Seok;Seo, Hee-Ju
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2020.07a
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    • pp.317-318
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    • 2020
  • 본 논문에서는 얼굴검출 후 MobilnetV2의 방법을 이용하여 적은 연산량으로 CCTV가 실시간으로 마스크 착용 유무를 판단할 수 있는 방법을 제시하였다. 이를 통해 현재 이슈가 되고있는 코로나19 등 전염병의 전염 위험이 있는 주요 장소에서 인공지능 CCTV가 마스크 미착용자를 식별해 알려줌으로써 마스크 미착용자를 관리할 수 있는 방법을 제공하였다.

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Object Recognition Using Convolutional Neural Network in military CCTV (합성곱 신경망을 활용한 군사용 CCTV 객체 인식)

  • Ahn, Jin Woo;Kim, Dohyung;Kim, Jaeoh
    • Journal of the Korea Society for Simulation
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    • v.31 no.2
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    • pp.11-20
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    • 2022
  • There is a critical need for AI assistance in guard operations of Army base perimeters, which is exacerbated by changes in the national defense and security environment such as force reduction. In addition, the possibility for human error inherent to perimeter guard operations attests to the need for an innovative revamp of current systems. The purpose of this study is to propose a real-time object detection AI tailored to military CCTV surveillance with three unique characteristics. First, training data suitable for situations in which relatively small objects must be recognized is used due to the characteristics of military CCTV. Second, we utilize a data augmentation algorithm suited for military context applied in the data preparation step. Third, a noise reduction algorithm is applied to account for military-specific situations, such as camouflaged targets and unfavorable weather conditions. The proposed system has been field-tested in a real-world setting, and its performance has been verified.

Home Monitoring CCTV by using deep learning (딥러닝을 활용한 가정 모니터링 CCTV)

  • Kim, Ah-Lynne;Lee, Eun-Ji;Kwon, Hye-young;Baek, Hye-Min
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.960-963
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    • 2020
  • 소비자원 소비자 위해 정보 동향 분석 보고서에 따르면, 10대 미만과 60대 이상이 겪는 사고 중 가정 내 사고의 비율이 약 70%로 높은 비율을 차지하는 것을 볼 수 있다. 기존의 CCTV는 실시간으로 영상 전송은 가능하지만 영상 속의 상황 분석은 하지 못하며, 이를 위해선 지켜보는 인력이 추가로 필요하다. 따라서 보호자의 비용 부담 없이 24시간 행동 분석을 통해 보호가 필요한 가족 구성원의 사고를 예방할 수 있으며 침입과 같은 범죄를 막을 수 있는 AI CCTV의 필요성을 느껴 제작하였다. 해당 CCTV는 실시간 분석으로 영상 내의 위험을 감지하고 감지 후 관련 사항을 등록된 연락처로 송출해서 보호자에게 위험 상황을 알릴 수 있다. 향후 가정 내의 IOT 기기들과 연결하여 위험 상황 발생 시 직접 위험 상황을 해결할 수 있는 스마트 홈 보안으로 범위를 넓힐 수 있다.

AI Self-driving CCTV System for Smartening Crime Prevention Facilities (방범 설비의 스마트화를 위한 인공지능 자율주행 CCTV 시스템)

  • Yeon-Kyu Kwak;Ye-Jin Kim;Jin-Woo Woo;Dong-Gyu Jung;Sang-Oh Yoo
    • 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.

Location Tracking and Visualization of Dynamic Objects using CCTV Images (CCTV 영상을 활용한 동적 객체의 위치 추적 및 시각화 방안)

  • Park, Sang-Jin;Cho, Kuk;Im, Junhyuck;Kim, Minchan
    • Journal of Cadastre & Land InformatiX
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    • v.51 no.1
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    • pp.53-65
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    • 2021
  • C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

집중탐구 - 닭·오리 농장·부화장에 CCTV 의무설치

  • 한국오리협회
    • Monthly Duck's Village
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    • s.194
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    • pp.18-23
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    • 2019
  • 7월 1일부터 조류인플루엔자(AI) 등 가축전염병에 신속히 대응할 수 있도록 닭 오리 농장에 폐쇄회로(CCTV) 설치가 의무화된다. 살충제 사용을 위반한 산란계 농가는 전문 업체를 통한 해충 방제를 의무적으로 실시해야 한다. 농어촌에 거주하면서 영농 창업을 희망하는 비(非)농업인도 귀농인에 준해 창업이나 주택 구입 등에 필요한 자금을 지원받을 수 있게 됐다. 농식품 계열 대학에 재학 중인 고학년 학생들은 졸업 후 농업분야 취 창업을 조건으로 등록금 전액을 지원받을 수 있는 장학금에 도전해볼 수 있다. 기획재정부가 내놓은 농림축산식품부 소관 '2019년 하반기 달라지는 주요 제도'를 소개한다.

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Escape Route Prediction and Tracking System using Artificial Intelligence (인공지능을 활용한 도주경로 예측 및 추적 시스템)

  • Yang, Bum-Suk;Park, Dea-Woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.8
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    • pp.1130-1135
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    • 2022
  • In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office has built a control center for CCTV control and is performing 24-hour CCTV video control for the safety of citizens. Seoul Metropolitan Government is building a smart city integrated platform that is safe for citizens by providing CCTV images of the ward office to enable rapid response to emergency/emergency situations by signing an MOU with related organizations. In this paper, when an incident occurs at the Seoul Metropolitan Government Office, the escape route is predicted by discriminating people and vehicles using the AI DNN-based Template Matching technology, MLP algorithm and CNN-based YOLO SPP DNN model for CCTV images. In addition, it is designed to automatically disseminate image information and situation information to adjacent ward offices when vehicles and people escape from the competent ward office. The escape route prediction and tracking system using artificial intelligence can expand the smart city integrated platform nationwide.

A Study on Mobile CCTV for Geofence Monitoring for Construction Safety (건설 안전용 지오펜스 감시를 위한 이동형 CCTV 연구)

  • Kang, Aetti;Kim, Sangwoo;Baek, Eunjin;Lee, Jisoo;Eom, Semin;Ham, Sungil
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2023.05a
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    • pp.381-382
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    • 2023
  • Frequent accidents occur when workers at construction sites leave the safety zone, and particularly in the past 5 years, 9 fatal accidents occurred at the Korea Railroad Corporation due to train accidents on other tracks during track work. With the Severe Accident Punishment Act taking effect in January 2022, it is a priority to secure a safe work environment for workers at industrial (construction) sites. Therefore, there is a need to manage workers' departure from the safety zone (construction zone) and to facilitate communication within the construction zone. In this study, a mobile edge computing CCTV system is proposed that uses geofencing to determine whether workers are working in the danger zone, which can judge and respond in real-time to the ever-changing field environment. The proposed system is mobile and flexible, rather than server-based fixed CCTV. However, since it is designed mainly based on images, it has limitations in recognition rate depending on the environment such as distance, viewing angle, and illumination. As a way to compensate for this, it is required to develop more reliable equipment by combining technologies such as LiDAR and Radar.

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Where and Why? A Novel Approach for Prioritizing Implementation Points of Public CCTVs using Urban Big Data

  • Ji Hye Park;Daehwan Kim;Keon Chul Park
    • Journal of Internet Computing and Services
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    • v.24 no.5
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    • pp.97-106
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    • 2023
  • Citizens' demand for public CCTVs continues to rise, along with an increase in variouscrimes and social problems in cities. In line with the needs of citizens, the Seoul Metropolitan Government began installing CCTV cameras in 2010, and the number of new installations has increased by over 10% each year. As the large surveillance system represents a substantial budget item for the city, decision-making on location selection should be guided by reasonable standards. The purpose of this study is to improve the existing related models(such as public CCTV priority location analysis manuals) to establish the methodology foranalyzing priority regions ofSeoul-type public CCTVs and propose new mid- to long-term installation goals. Additionally, using the improved methodology, we determine the CCTV priority status of 25 autonomous districts across Seoul and calculate the goals. Through its results, this study suggests improvements to existing models by addressing their limitations, such as the sustainability of input data, the conversion of existing general-purpose models to urban models, and the expansion of basic local government-level models to metropolitan government levels. The results can also be applied to other metropolitan areas and are used by the Seoul Metropolitan Government in its CCTV operation policy

A Methodology for Making Military Surveillance System to be Intelligent Applied by AI Model (AI모델을 적용한 군 경계체계 지능화 방안)

  • Changhee Han;Halim Ku;Pokki Park
    • Journal of Internet Computing and Services
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    • v.24 no.4
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    • pp.57-64
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    • 2023
  • The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.