• Title/Summary/Keyword: Open-street CCTV

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The Crime-reduction Effects of Open-Street CCTV around Elementary Schools (초등학교 주변 방범용CCTV의 범죄감소효과 연구)

  • Lim, Hyung-Jin
    • Korean Security Journal
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    • no.51
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    • pp.199-219
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    • 2017
  • This research examined the degree to which open-street closed-circuit television (CCTV) systems reduced crime in the vicinity of elementary schools. Information including crime dates, locations, and types around nine elementary schools in the city of Chuncheon in South Korea where the cameras had been installed was gathered and assessed. By employing the Poisson regression with "month" as the unit of analysis and controlling for the days in each month, the average monthly temperatures, and crime trends, the research results show that the CCTV installations had an impact on the reduction of total crime and serious crime. However, the same reduction effect was not observed for disorder crime. Therefore, the results of this study suggest that the employing CCTV is an effective way to control overall crime rates, especially serious crime.

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Threat Situation Determination System Through AWS-Based Behavior and Object Recognition (AWS 기반 행위와 객체 인식을 통한 위협 상황 판단 시스템)

  • Ye-Young Kim;Su-Hyun Jeong;So-Hyun Park;Young-Ho Park
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.4
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    • pp.189-198
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    • 2023
  • As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.