• Title/Summary/Keyword: 예측치안

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치안분야에서의 Big Data 활용 사례와 바람직한 공공 연구조직 설계

  • Gwon, Hyo-Jin;Lee, Jang-Jae
    • Proceedings of the Korea Technology Innovation Society Conference
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    • 2017.11a
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    • pp.1245-1262
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    • 2017
  • 최근 범죄예측, 교통관리, 신원확인 등 다양한 목적으로 치안 분야에서 ICT 기술이 개발 이용되고 있다. 사물인터넷의 등장으로 인해 생성되는 데이터의 양이 폭발적으로 증가하고 있으며, 이를 통해 만들어진 빅데이터는 범죄분석 및 예방, 치안수요의 예측, 범죄 수사에 있어서 새로운 변화를 가져올 것으로 예고되고 있다. 새롭게 부각된 치안분야에서의 빅데이터 활용 서비스 사례로는 범죄 예측 서비스, 교통 관련 서비스, 영상 분석과 통합 관제 서비스, 웨어러블 폴리스캠 활용서비스, 신원 확인(바이오 인식 기술)서비스 등이 있다. 선진국에서는 이들 서비스를 개발하고 활용하기 위한 다양한 공공 연구조직이 설립되어 운영되고 있다. 본 고에서는 치안분야에서 빅데이터를 기반으로 한 국내외 서비스 사례와 함께 이를 수용하기 위한 바람직한 공공 연구조직에 대한 논의를 전개한다.

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Trend of Science Policing-based Preemptive Correspondence Police Service Technology (과학치안 기반 선제 대응 치안서비스 기술 동향)

  • Park, Y.S.;Kim, S.H.;Park, W.J.;Baek, M.S.;Lee, Y.T.
    • Electronics and Telecommunications Trends
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    • v.36 no.5
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    • pp.74-81
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    • 2021
  • Based on data provided by the science and technology knowledge infrastructure (ScienceON, 2017-2021), this paper reviews the research trends of domestic police services and related technologies, and describes the research and development direction of policing technology. For this purpose, the research was searched using the keywords science policing, smart policing, predictive policing, and policing. Policing technology is used for crime investigation (prevention), such as crime analysis and crime prediction. The collection of related data use urban infrastructure, the processing of data collected using technologies, such as artificial intelligence, and the utilization of data in police services (system) were summarized. In future, on-site support technology and crime investigation (prevention) technology for a preemptive correspondence to social threats and effective police activities must be developed. In addition, the quality of police services should be improved, a system to use police-related data should be developed, and the capabilities of police experts need to be strengthened.

경찰관서 표준인력 수요모델 개발;시스템다이내믹스 방법론을 기반으로

  • Jeong, Jae-Rim;Jeon, So-Yeon;Gwak, Mi-Ae;Yeon, Seung-Jun
    • 한국경영정보학회:학술대회논문집
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    • 2007.06a
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    • pp.843-848
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    • 2007
  • 날로 광역화, 지능화, 디지털화된 범죄양상과 국민들의 고품질 치안서비스에 대한 관심과 욕구의 증대로 인해 치안수요가 증가하고 있다. 지금까지의 선행연구들은 경찰인력의 수요에 영향을 미치는 특정 변수를 회귀분석을 통해 찾아낸 뒤 이것을 바탕으로 경찰인력에 대한 예측을 시도하였으나, 경찰 업무 전반에 걸친 직무를 분석하여 치안 수요 및 업무량에 따른 적정인력을 산출하는 연구는 부족한 실정이다. 따라서 본 연구는 경찰관서 각 기능별 실무자 면담을 통해 직무를 분석한 후 기능별 주요 업무를 선정하였고 시스템 다이내믹스 방법론을 활용하여 기능별 경찰관서의 표준인력 수요를 예측하였다. 또한 235개의 관서 모델을 만들어 컴퓨터 시뮬레이션을 통해 관서별, 지방청별 효율적 인력 운용 방안에 대해 논의하였다.

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Information and Communications Technology in the Field of Public Security: Crime Prevention and Response System (치안분야의 정보통신기술 활용방안 연구 - 빅데이터기반 치안수요분석과 대응체계를 중심으로 -)

  • Kim, Yeon Soo
    • Convergence Security Journal
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    • v.16 no.6_2
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    • pp.23-32
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    • 2016
  • Rapid advances in information and communications technology are new challenges and also opportunities for the police. For the purpose of identifying its implications, this study reviews utilization cases of information and communications technology in the field of public security in South Korea and other countries. As theoretical basis for utilization of information and communications technology, this study introduces intelligence-led policing, predictive policing and evidence-based policing. Also, utilization of big-data based crime analysis and crime prediction technology, as well as advancement of information and communications system and command and control technology of the police, are discussed. Based on the identified implications in this study, the following proposals are made. They are (1) procuring basic data, (2) creating an integrated database, (3) increasing utilization of policy decision-makers, (4) exchange and cooperation between related institutions, (5) training professional analyzers, (6) establishing legal basis and practical guidelines for an integrated database.

A Study on Collaboration between the Public Law Enforcement and Private Security Sector for the Activation of Security (민간경비 활성화와 공경비와의 민간경비 협력증대방안)

  • Lim, Myeong-Soon
    • Korean Security Journal
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    • no.10
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    • pp.273-292
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    • 2005
  • The purpose of this study was to delve into all sorts of literature concerned in a bid to suggest how the Public Law Enforcement and private Security sector could join forces in preventing crimes and guaranteeing the safety of people. Quite naturally, crime has increased greatly to become one of the major social problems. Crime has been conventionally recognized as 'something' to be prevented and controlled by public law enforcement. However, the rate of crime increase has been so rapid that public law enforcement alone could not effectively control the everincreasing and diversified crimes in our society. To serve as a qualified partner for the police, private security industry should strive to secure excellent manpower and provide education for workers to improve their qualifications. Specifically, they should put sustained efforts into diversifying the types of security business and creating a new market to extend their scope of business and become more competitive. Intensified collaboration between the Public Law Enforcement and private Security security sector is expected to create new synergy in addressing people's needs for safety and enhancing their quality of life.

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Manpower Demand Forecasting in Private Security Industry (민간경비 산업의 인력수요예측)

  • Kim, Sang-Ho
    • Korean Security Journal
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    • no.19
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    • pp.1-21
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    • 2009
  • Manpower demand forecasting in private security industry can be used for both policy and information function. At a time when police agencies have fewer resources to accomplish their goals, forming partnership with private security firms should be a viable means to choose. But without precise understanding of each other, their partnership could be superficial. At the same time, an important debate is coming out whether security industry will continue to expand in numbers of employees, or level-off in the near future. Such debates are especially important for young people considering careers in private security industry. Recently, ARIMA model has been widely used as a reliable instrument in the many field of industry for demand forecasting. An ARIMA model predicts a value in a response time series as a linear combination of its own past values, past errors, and current and past values of other time series. This study conducts a short-term forecast of manpower demand in private security industry using ARIMA model. After obtaining yearly data of private security officers from 1976 to 2008, this paper are forecasting future trends and proposing some policy orientations. The result shows that ARIMA(0, 2, 1) model is the most appropriate one and forecasts a minimum of 137,387 to maximum 190,124 private security officers will be needed in 2013. The conclusions discuss some implications and predictable changes in policing and coping strategies public police and private security can take.

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A Study on the Characteristics of the Elderly Victims of Crime (범죄피해 노인의 특성에 관한 연구)

  • Sim, Hye-In
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2022.10a
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    • pp.325-326
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    • 2022
  • 통계청에 의하면 65세 이상 인구가 2024년 1,000만명을 도래할 것으로 예측하고 있으며, 노인인구 증가와 함께 노인치안 이슈들은 매년 증가하고 있다. 특히, 경찰청 자료에 따르면 최근 5년간 노인범죄피해는 매년 증가하고 있는 것으로 나타났다(경찰청, 2021). 치안서비스 대상에서 주요한 영역을 차지하게 될 노인을 대상으로 한 범죄예방정책을 마련하기 위하여 범죄피해노인의 특성에 관한 연구를 함에 있어 연도별 노인의 범죄피해영향요인의 차이가 있는지를 이 연구에서는 분석하고자 하였다. 따라서 이 연구에서는 한국형사·법무정책연구원의 2014년, 2016년, 2018년 전국범죄피해조사 2차 자료를 활용하였으며, 그 중 만65세 노인대상 자료만을 추출하여 2014년 1.921명, 2016년, 2,935명, 2018년 2,707명을 각각 최종분석에 활용하였다. Spss ver 21. 통계프로그램을 활용하여 로지스틱회귀분석을 실시하였으며, 연구결과 2014년에는 사회적 무질서 수준과 노인범죄피해와의 관계성이 높았다면, 2016년에는 물리적 무질서 수준과 노인범죄피해와의 관계성이 높았고, 2016년과 2018년에는 독거노인과 빈 집으로 가구가 노출되는 시간이 긴 정도가 노인범죄피해와의 관계성이 높은 것으로 볼 수 있었다. 이러한 연도별 노인 범죄피해 영향요인의 변화를 실증연구를 통해 검증함으로써 추후 노인범죄예방을 위한 정책마련의 자료로 활용하고자 한다.

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The Data-based Prediction of Police Calls Using Machine Learning (기계학습을 활용한 데이터 기반 경찰신고건수 예측)

  • Choi, Jaehun
    • The Journal of Bigdata
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    • v.3 no.2
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    • pp.101-112
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    • 2018
  • The purpose of the study is to predict the number of police calls using neural network which is one of the machine learning and negative binomial regression, by using the data of 112 police calls received from Chungnam Provincial Police Agency from June 2016 to May 2017. The variables which may affect the police calls have been selected for developing the prediction model : time, holiday, the day before holiday, season, temperature, precipitation, wind speed, jurisdictional area, population, the number of foreigners, single house rate and other house rate. Some variables show positive correlation, and others negative one. The comparison of the methods can be summarized as follows. Neural network has correlation coefficient of 0.7702 between predicted and actual values with RMSE 2.557. Negative binomial regression on the other hand shows correlation coefficient of 0.7158 with RMSE 2.831. Neural network has low interpretability, but an excellent predictability compared with the negative binomial regression. Based on the prediction model, the police agency can do the optimal manpower allocation for given values in the selected variables.

Study on abnormal behavior prediction models using flexible multi-level regression (유연성 다중 회귀 모델을 활용한 보행자 이상 행동 예측 모델 연구)

  • Jung, Yu Jin;Yoon, Yong Ik
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.1
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    • pp.1-8
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    • 2016
  • In the recently, violent crime and accidental crime has been generated continuously. Consequently, people anxiety has been heightened. The Closed Circuit Television (CCTV) has been used to ensure the security and evidence for the crimes. However, the video captured from CCTV has being used in the post-processing to apply to the evidence. In this paper, we propose a flexible multi-level models for estimating whether dangerous behavior and the environment and context for pedestrians. The situation analysis builds the knowledge for the pedestrians tracking. Finally, the decision step decides and notifies the threat situation when the behavior observed object is determined to abnormal behavior. Thereby, tracking the behavior of objects in a multi-region, it can be seen that the risk of the object behavior. It can be predicted by the behavior prediction of crime.

Production Data Analysis to Predict Production Performance of Horizontal Well in a Hydraulically Fractured CBM Reservoir (수압파쇄된 CBM 저류층에서 수평정의 생산 거동예측을 위한 생산자료 분석)

  • Kim, Young-Min;Park, Jin-Young;Han, Jeong-Min;Lee, Jeong-Hwan
    • Journal of the Korean Institute of Gas
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    • v.20 no.3
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    • pp.1-11
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    • 2016
  • Production data from hydraulically fractured well in coalbed methane (CBM) reservoirs was analyzed using decl ine curve analysis (DCA), flow regime analysis, and flowing material balance to forecast the production performance and to determine estimated ultimate recovery (EUR) and timing for applying the DCA. To generate synthetic production data, reservoir models were built based on the CBM propertie of the Appalachian Basin, USA. Production data analysis shows that the transient flow (TF) occurs for 6~16 years and then the boundary dominated flow (BDF) was reached. In the TF period, it is impossible to forecast the production performance due to the significant errors between predicted data and synthetic data. The prediction can be conducted using the production data of more than a year after reached BDF with EUR error of approximately 5%.