• Journal of the Korea Society of Computer and Information
• /
• v.22 no.1
• /
• pp.41-48
• /
• 2017

In this study, we proposed GIS-based Regional Crime Prevention Index (RCPI) development method designed to support local governments with systematic crime prevention activities. The public interest in safe urban environment is increasing rapidly. The government is putting efforts into crime prevention activities to eliminate the criminal opportunities in advance. CPTED is method to prevent crimes in the city by improving environmental factors that cause crime. It is used by local governments to promote the crime prevention activities centering on the expansion of CCTVs and street lamps and the improvement of street environment. However, most policies were terminated as one-off programs and it is necessary to monitor the effect of such policies on a continuous basis. In order to alleviate issues, this study proposed RCPI as part of crime safety assessment in urban environments. The estimation of RCPI in City A of Gyeonggi-do showed relative differences in 31 districts (dong), indicating that it is also possible to evaluate the crime safety in the local community on the level of the administrative dong, the smallest administrative district in the urban environments. As a crime map, the RCPI will be used effectively as he reference to support the decision making process for local government in the future.

• Journal of the Korean Geographical Society
• /
• v.36 no.3
• /
• pp.329-341
• /
• 2001

The purpose of this study focused on the distribution of crimes in Cheongju City. This study emphasized the characteristics of place and spatial pattern of crime in Central Business District(CBD). The crime core areas were delineated and explained through land-use based on fieldwork and GIS analysis For this aim. the police crime data of Cheongju Dongbu(east). Seobu(west) for 1998 were collected In which 3.909 indictable or similar offenses were reported. In this study, Included climes are murder. rape, robbery. arson, theft, burglary, assault and vandalism. Because theme crimes are related with site-specific crime. As a result. land-use patterns are often related to specific type of offenses. The climes in Cheongju City were concentrated in the CBD Most crimes were assaults and thefts Crime areas can be classified by the age of the offender Around Chungang and Pungmul Market in the CBD. the offender＇s ages were 30-50 dominantly Assaults and thefts were concentrated in Songan-gil(street). which is a place teen-ages and youngsters meet frequently The result of the buffering analysis with roads, explained 40% of crime within a 30m buffer area( including both sides) of a principal road The rest of the climes mainly occurred in the vicinity of narrow streets and alleys.

• Journal of Internet Computing and Services
• /
• v.24 no.6
• /
• pp.99-105
• /
• 2023

In the 4th industrial revolution, the field of criminal justice is paying attention to Legaltech using artificial intelligence to provide efficient legal services. This paper attempted to create a crime prediction model that can apply Recurrent Neural Network(RNN) to increase the potential for using legal technology in the domestic criminal justice field. To this end, the crime process was divided into pre, during, and post stages based on the criminal facts described in the judgment, utilizing crime script analysis techniques. In addition, at each time point, the method and evidence of crime were classified into objects, actions, and environments based on the sentence composition elements and the 8 principles of investigation. The case summary analysis framework derived from this study can contribute to establishing situational crime prevention strategies because it is easy to identify typical patterns of specific crime methods. Furthermore, the results of this study can be used as a useful reference for research on generating crime situation prediction data based on RNN models in future follow-up studies.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.12 no.1
• /
• pp.12-25
• /
• 2009

The aim of this study is to analyze the periodical and spatial characteristics of urban crime and to find out the factors that affect the crime occurrence. For these, crime data of Masan City was examined and crime occurrence pattern is ploted on a map using crime density and criminal hotspot analysis. The spatial relationship of crime occurrence and factors affecting crime were also investigated using ESDA (Exploratory Spatial Data Analysis) and SAR (Spatial Auto-Regression) model. As a result, it was found that crimes had strong tendency of happening during a certain period of time and with spatial contiguity. Spatial contiguity of crimes was made clear through the spatial autocorrelation analysis on 5 major crimes. Especially, robbery revealed the highest spatial autocorrelation. However as a autocorrelation model, Spatial Error Model(SEM) had statistically the highest goodness of fit. Moreover, the model proved that old age population ratio, property tax, wholesale-retail shop number, and retail & wholesale number were statistically significant that affect crime occurrence of 5 most major crimes and theft crime. However population density affected negatively on assault crime. Lastly, the findings of this study are expected to provide meaningful ideas to make our cities safer with U-City strategies and services.

• Journal of Satellite, Information and Communications
• /
• v.10 no.2
• /
• pp.40-45
• /
• 2015

In this paper, we proposed and implemented a crime prediction algorithm based upon crime influential factors. To collect the crime-related big data, we used a data which had been collected and was published in the supreme prosecutors' office. The algorithm analyzed various crime patterns in Seoul from 2011 to 2013 using the spatial statistics analysis. Also, for the crime prediction algorithm, we adopted a Bayesian network. The Bayesian network consist of various spatial, populational and social characteristics. In addition, for the more precise prediction, we also considered date, time, and weather factors. As the result of the proposed algorithm, we could figure out the different crime patterns in Seoul, and confirmed the prediction accuracy of the proposed algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.5
• /
• pp.217-221
• /
• 2017

Proactive prevention is important for crime. Past crimes have focused on coping after death and punishing them. But with Big Data technology, crime can be prevented spontaneously. Big data can predict the behavior of criminals or potential criminals. This article discusses how to build a big data system for crime prevention. Specifically, it deals with the way to combine unstructured data of big data with basic form data, and as a result, designs crime prevention system. Through this study, it is expected that the possibility of using big data for crime prevention is described through fingerprints, and it is expected to help crime prevention program and research in future.

• Journal of Korea Game Society
• /
• v.11 no.2
• /
• pp.69-79
• /
• 2011

Online game industry and item trade have grown up fast after 2000. And there has been a perspective that online game and item trade are the cause of the crimes, especially cyber crime like hacking, virus. But there was no positive research about the opinion, so this article studies the relations among online game, item trade and crime. The results suggest that online game and item trade maybe a cause of cyber crime and property crime. But online game and item trade don't increase the total number of crime. That means that online game and item trade substitute the way how crime happens. Online game and item trade substitute no-property crime to property crime.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.4
• /
• pp.78-89
• /
• 2012

The purpose of this study is to examine the possibility of crime prevention in consideration of urban physical environment by analyzing the spatial distribution characteristics and pattern using actual crime occurrence data of the case city. The crime data was rebuilt by transforming them into geographic information system to analyze the spatial aspect of crime occurrence. The findings are as follows: a change from 2008 to 2011 is indicated with similar trend. But the local movements of crime hot spots are found. Moreover crimes were happening along the roads in linear pattern rather than inside of blocks in commercial area. This indicates the importance of environmental improvement of roads and open spaces. In addition it was found that the crime occurrence in a dangerous district can be reduced and prevented through the physical environment design and urban planning. The findings will contribute to promoting fundamental crime prevention as the physical environmental improvement in a city and to building a safe community as its result.

• Journal of the Korea Convergence Society
• /
• v.11 no.11
• /
• pp.75-80
• /
• 2020

Since the Fourth Industrial Revolution, important technologies such as big data analysis, robotics, Internet of Things, and the artificial intelligence have been used in various fields. Generally speaking it is understood that the big-data technology consists of gathering stage for enormous data, analyzing and processing stage and distributing stage. Until now crime records which is one of useful big-sized data are utilized to obtain investigation information after occurring crimes. If crime records are utilized to predict crimes it is believed that crime occurring frequency can be lowered by processing big-sized crime records in big-data framework. In this research the design is proposed that the smart system can provide the users of smart devices crime occurrence probability by processing crime records in big-data analysis. Specifically it is meant that the proposed system will guide safer routes by displaying crime occurrence probabilities on the digital map in a smart device. In the experiment result for a smart application dealing with small local area it is showed that its usefulness is quite good in crime prevention.

• Korean Security Journal
• /
• no.45
• /
• pp.221-242
• /
• 2015

Verification for the causality of factors affecting fear of criminal victim which has a bad influence on the senior's quality of life and directions to prevent the crimes against the elderly have been suggested. This study proves the applicability for fear of crime to old people especially based on risk interpretation model consisting of perceived risk of crime, behavioral response and fear of crime. Analysis results are as follows. First, disorder factors as social characteristics showed statistically significant influences on perceived risk of crime, behavioral response and fear of crime. Second, direct experienced crime victimization only affected perceived risk of crime while indirect experienced crime victimization had an effect on perceived risk of crime and fear of crime as well. Third, perceived risk of crime influenced fear of crime. Fourth, perceived risk of crime was concerned with fear of crime. Fifth, behavioral response was affiliated with fear of crime. These results reveal that risk interpretation model can be applied to senior's fear of crime. Moreover, disorder factor as social characteristic and experienced crime victimization as individual characteristic help the elderly perceive the risk of crime, bring behavioral response. Consequently, they play a role of factors affecting fear of crime. It is emphasized that support policy is required for the elderly who had experienced crime and stabilization of community environment if necessary to improve the quality of life.