• Title/Summary/Keyword: Crime prediction

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Crime prediction Model with Moving Behavior pattern (행동 패턴 기반 범죄 예측 모델 연구)

  • Choe, Jong-Won;Choi, Ji-Hyen;Yoon, Yong-Ik
    • Journal of Satellite, Information and Communications
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    • v.11 no.1
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    • pp.55-57
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    • 2016
  • In this paper, we present an algorithm to determine the abnormal behavior through a CCTV-based behavioral recognition and a pattern of hand using ConvexHull. In the existing way that using CCTV for crime prevention, facial recognition is mainly used. Facial recognition is the way that compares the faces that are seen on the screen and faces of criminals for determining how dangerous targets are, however, this way is hard to predict future criminal behavior. Therefore, to predict more various situations, abnormal behaviours are determined with targets' incline of arms, legs and bodys and patterns of hand movements. it can forecast crimes when an acting has been getting within common normality out, comparing whose acting patterns with the crime patterns.

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.

Extraction of Crime Vulnerable Areas Using Crime Statistics and Spatial Big Data (공간 빅데이터와 범죄통계자료를 이용한 범죄취약지 추출)

  • Park, So-Rang;Park, Jae-Kook
    • Journal of Convergence for Information Technology
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    • v.8 no.1
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    • pp.161-171
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    • 2018
  • This study set out to identify crime vulnerable areas with the GIS spatial analysis technique for the prediction of crimes. Crime vulnerable areas were extracted from the statistics of crimes with the GIS hotspot analysis technique and the inverse distance weighted(IDW) method applied to different crimes according to places and use districts. The scope of surveillance and weight were calculated for each of CPTED surveillance elements including CCTV, streetlamp, patrol division, and police substation. Maps of crime vulnerable areas were overlapped one after another to make a CPTED-based one expressed in four grades(safety, attention, warning, and risk).

DNA methylation-based age prediction from various tissues and body fluids

  • Jung, Sang-Eun;Shin, Kyoung-Jin;Lee, Hwan Young
    • BMB Reports
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    • v.50 no.11
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    • pp.546-553
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    • 2017
  • Aging is a natural and gradual process in human life. It is influenced by heredity, environment, lifestyle, and disease. DNA methylation varies with age, and the ability to predict the age of donor using DNA from evidence materials at a crime scene is of considerable value in forensic investigations. Recently, many studies have reported age prediction models based on DNA methylation from various tissues and body fluids. Those models seem to be very promising because of their high prediction accuracies. In this review, the changes of age-associated DNA methylation and the age prediction models for various tissues and body fluids were examined, and then the applicability of the DNA methylation-based age prediction method to the forensic investigations was discussed. This will improve the understandings about DNA methylation markers and their potential to be used as biomarkers in the forensic field, as well as the clinical field.

A Deep Learning-based Streetscapes Safety Score Prediction Model using Environmental Context from Big Data (빅데이터로부터 추출된 주변 환경 컨텍스트를 반영한 딥러닝 기반 거리 안전도 점수 예측 모델)

  • Lee, Gi-In;Kang, Hang-Bong
    • Journal of Korea Multimedia Society
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    • v.20 no.8
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    • pp.1282-1290
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    • 2017
  • Since the mitigation of fear of crime significantly enhances the consumptions in a city, studies focusing on urban safety analysis have received much attention as means of revitalizing the local economy. In addition, with the development of computer vision and machine learning technologies, efficient and automated analysis methods have been developed. Previous studies have used global features to predict the safety of cities, yet this method has limited ability in accurately predicting abstract information such as safety assessments. Therefore we used a Convolutional Context Neural Network (CCNN) that considered "context" as a decision criterion to accurately predict safety of cities. CCNN model is constructed by combining a stacked auto encoder with a fully connected network to find the context and use it in the CNN model to predict the score. We analyzed the RMSE and correlation of SVR, Alexnet, and Sharing models to compare with the performance of CCNN model. Our results indicate that our model has much better RMSE and Pearson/Spearman correlation coefficient.

Data mining approach to predicting user's past location

  • Lee, Eun Min;Lee, Kun Chang
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.11
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    • pp.97-104
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    • 2017
  • Location prediction has been successfully utilized to provide high quality of location-based services to customers in many applications. In its usual form, the conventional type of location prediction is to predict future locations based on user's past movement history. However, as location prediction needs are expanded into much complicated cases, it becomes necessary quite frequently to make inference on the locations that target user visited in the past. Typical cases include the identification of locations that infectious disease carriers may have visited before, and crime suspects may have dropped by on a certain day at a specific time-band. Therefore, primary goal of this study is to predict locations that users visited in the past. Information used for this purpose include user's demographic information and movement histories. Data mining classifiers such as Bayesian network, neural network, support vector machine, decision tree were adopted to analyze 6868 contextual dataset and compare classifiers' performance. Results show that general Bayesian network is the most robust classifier.

A Study on the Use of Criminal Justice Information Big Data in terms of the Structuralization and Categorization (형사사법정보의 빅데이터 활용방안 연구: 구조화 범주화 관점으로)

  • Kim, Mi Ryung;Roh, Yoon Ju;Kim, Seonghun
    • Journal of the Korean Society for information Management
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    • v.36 no.4
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    • pp.253-277
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    • 2019
  • In the era of the 4th Industrial Revolution, the importance of data is intensifying, but there are many cases where it is not easy to use data due to personal information protection. Although criminal justice information is expected to have various useful values such as crime prediction and prevention, scientific investigation of criminal investigations, and rationalization of sentencing, the use of criminal justice information is currently limited as a matter of legal interpretation related to privacy protection and criminal justice information. This study proposed to convert criminal justice information into 'crime data' and use it as big data through the structuralization and categorization of criminal justice information. And when using "crime data," legal issues, value in use, considerations for data generation and use were verified by experts, and future strategic development plans were identified. Finally we found that 'crime data' seems to have solved the privacy problem, but it is necessary to specify in the criminal justice information related law and it is urgent to be organized in a standardized form for analysis to use big data. Future directions are to derive data elements, construct a dictionary thesaurus, define and classify personal sensitive information for data grading, and develop algorithms for shaping unstructured data.

Current Status of Response to Digital Child Sexual Slavery and Comparative Analysis of Overseas Crime Prediction System Using Artificial Intelligence (디지털 아동 성착취 대응현황과 해외 인공지능 범죄 예측 시스템 비교분석)

  • Kim, Hyejin
    • Journal of Digital Convergence
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    • v.18 no.7
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    • pp.357-368
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    • 2020
  • This study identifies the aspects and characteristics of 'Digital Sexual Crimes' that changed rapidly in recent years. It has identified the so-called "Telegram sexual harassment and exploitation" incident on the front page. We also want to analyze this and draw up policy suggestions that can help prepare social measures. In the wake of the Telegram sexual exploitation scandal, The National Assembly is quickly proposing related bills. However, the reality is that even a clear concept and definition of "Digital sexual Crimes" have not been made yet. The effective support system for victims is also insufficient. Therefore, this paper examines the definition and concept of child sexual exploitation and harassment. We will look at the features, causes, and conditions. In addition, it will examine the current status of Digital Sexual Crimes distribution and deletion of domestic, foreign platforms. Major foreign countries, including the U. S. A. refer to cases in which big data and artificial intelligence technologies are actively used to protect victims and track perpetrators.

Social Safety Systems through Big Data Analysis of Public Data (공공 데이터의 빅데이터 분석을 통한 사회 안전망 시스템)

  • Lee, Sun Yui;Jung, Jun Hee;Cha, Gyeong Hyeon;Son, Ki Jun;Kim, Sang Ji;Kim, Jin Young
    • Journal of Satellite, Information and Communications
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    • v.10 no.4
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    • pp.77-82
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    • 2015
  • This paper proposed an accident prediction model in order to prevent accidents in mountain areas using a big data analysis. Data of accidents in mountain areas are shown as graphs. We have analyzed cases: the number of accidents per year, day of week, time of day to find patterns of the negligent accident in mountain areas. The proposed prediction model consists of weighted variables of the accident in mountain through visualized big data analysis. The model of danger index performance is demonstrated by showing accident-prone areas with weighted variables.

A Study on the Development Plan of Smart City in Korea

  • KIM, Sun-Ju
    • The Journal of Economics, Marketing and Management
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    • v.10 no.6
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    • pp.17-26
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    • 2022
  • Purpose: This study analyzes advanced cases of overseas smart cities and examines policy implications related to the creation of smart cities in Korea. Research design, data, and methodology: Analysis standards were established through the analysis of best practices. Analysis criteria include Technology, Privacy, Security, and Governance. Results: In terms of technology, U-City construction experience and communication infrastructure are strengths. Korea's ICT technology is inferior to major countries. On the other hand, mobile communication, IoT, Internet, and public data are at the highest level. The privacy section created six principles: legality, purpose limitation, transparency, safety, control, and accountability. Security issues enable urban crime, disaster and catastrophe prediction and security through the establishment of an integrated platform. Governance issues are handled by the Smart Special Committee, which serves as policy advisory to the central government for legal system, standardization, and external cooperation in the district. Conclusions: Private technology improvement and participation are necessary for privacy and urban security. Citizens should participate in smart city governance.