• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.207-215
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• 2009

Recently, the research of the analysis of the crime spatial is increased by using the computer information technology and GIS (Geometric Information System) in order to prevent the urban crime so as to increase the urbanization rate. In this paper, a probability map formed by the raster is organized by the quantification of crime risk per the cell using the region property of the urban spatial information in the static environment. Also, a map of the risk probability is constructed based on the relative risk by the region property, the relative risk by the facility, the relative risk by the woody plant and the river, and so on. And, this integrated risk probability map is calculated by averaging the individual cell risk applied to the climatic influence and the seasonal factor. And, a probability map of the overall risk is generated by the interpretation key of the crime occurrence relative risk index, and so, this information is applied to the probability map quantifying the occurrence crime pattern. And so, in this paper, a methodology of the modeling and the simulation that this crime risk probability map is modified according to the passage of time are proposed.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.221-230
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• 2006

Changing drastically, the life in a modern city has forced citizens to gradually shorten their average period of settlement, which has weakened the identity of city habitation, thus causing serious crimes and damaging the security of city greatly. Haying a highly composite structure with not only macro, but micro characteristics, city is grasped as a very composite phenomenon shown in the social, economic and spatial constitution relationships, including the personal motives of criminals. Accordingly, this study puts stress on the necessity of any crime prediction program to predict the occurrence of crimes by analyzing the occurrence patterns of sharply increasing intra-city crimes of violence on a typical, time and spatial basis and clarifying their structural dynamic relationships in a both macro and micro manner. Moreover, the deduction of various factors closely related to crime occurrence will contribute to elucidating the occurrence structure of city crimes.

• Korean Journal of Culture and Social Issue
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• v.13 no.3
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• pp.127-153
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• 2007

The study aims to examine the effects of crime on societal anxiety. For this purpose, two studies were conducted. In study 1, the data were collected from 286 students(male 160, female 126) regarding perceived seriousness of crime, estimation of crime occurrence, societal anxiety, and estimation of change in these 3 variables every 3 years from 1993 to 2011. The means of the 3 variables were higher than the midpoint of the scale. And the means of all the 3 variables gradually increased from 1993 to 2011 and the change patterns were very similar. Furthermore, the estimation of crime occurrence and perceived seriousness of crime were significant predictors of societal anxiety. Study 2 was conducted to explore the effect of frequency estimation of the criminal acts on the societal anxiety. The data from 259 subjects(male 141, female 118) were analysed. The occurrence of frequency of 7 types of crimes including 25 criminal acts were estimated and societal anxiety was measured. The results of study 2 showed that only the major crime was significant a predictor of societal anxiety, and among the major crimes, arson was a significant predictor of the dependent variable. Implications and limits of the studies are discussed.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.357-360
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• 2008

The purpose of this research is to demonstrate the propriety of the locations of the Jigudea(police boxes) through time and spatial analysis. The study area was limited to BusanJingu of Busan city which includes Seo-myeon district; the biggest downtown in Busan city. In this case, monthly crime position occurrence number of times by time analysis, criminal occurrence number of times and the position have some similarities. In case of Jigudea(police boxes) which handle crime, throngs were piled up. The other case of position which crime, there is no Jigudea(police boxes) in group or two were situated. As a result, it is required that Jigudea(police boxes) in Jin-gu should be rearranged and relocated properly.

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

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.120-134
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• 2015

Under the hypothesis that the form of road network could affect crime occurrence, this study demonstrates to prove them using Space Syntax with real crime data. We calculated integration, control, connection index by means of Space Syntax and analyzed the relationship between the three indexes and the number of crime occurrence on the each road. Next, in order to generalize the analysis results we adopted Multi-Agent Model and simulated several scenarios on the computer virtual space. The results revealed that integration index has the strongest relationship with crime occurrence both in the case of real study area and virtual space simulations. Though this study has several limitations on the extent of virtual space and realistic computer programming of agents' behavior, the results are meaningful to verify the relationship between the form of read network and crime occurrence. Moreover the simulation platform that this study developed has promising possibilities to find realistic solutions on the effective police deployment or facility layout to improve smart safe city development.

• Korean Security Journal
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• no.3
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• pp.175-204
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• 2000

In modern society, a spontaneous phenomenon that community residents' participation in crime prevention sphere is increasing now due to the recognition that it is extremely difficult to control crime only by the limited official power(police) is spreading in the society. In the consideration of crime occurrence, the fear of crime does not belong to a certain person any more, but it turns to a matter of common interest for all people. If the recognition of community problems is well understood and analysed, the effect of community residents' participation in crime prevention will appear more eminent and definite. For a long period of time, thanks to the community residents' participation in crime prevention, it has been possible to sustain safety and stability of local community. Ultimately not only the police could reduce the crime problems but local community could decrease a fear of crime. In this study, for maximized effect of crime prevention, it is focused on the role of the community residents' participation in crime prevention. For desirable interrelations among service group and residents, police, first the review of situational crime prevention and community crime prevention theory was studied. And the community residents participation to crime prevention activity in U.S.A, Japan etc was reviewed. By interviewing actual participants in community crime prevention activity, the problems and countermeasures of the community residents' participation in crime prevention activity and desirable direction was suggested

• Journal of the Korean housing association
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• v.25 no.3
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• pp.85-92
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• 2014

The purpose of this study is to explore the relationship between housing types and crime and to suggest the appropriate strategies and interventions of housing policies for crime prevention. For spatial analysis of crime data, spatial autocorrelation is tested by Moran's I Test. A Ordinary Least Squares-based regression model is employed because crime data used in this study fails to show spatial autocorrelation. Results show that housing type variables except non-residential housing type are not associated with crime. Among land-use characteristics, the percentage of commercial areas is likely to better explain crime occurrence rather than housing types. It is surprising that residents' satisfaction to housing environment has a positive direction in its relationship with crime even though it cannot have a statistical significance. However, fear of crime shows a negative direction with crime although it fails to have a statistical significance. The findings of this study can contribute to understand the association between housing types and crime when setting housing policies for crime prevention.

• KIEAE Journal
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• v.10 no.5
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• pp.77-85
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• 2010

The library is the most frequently utilized building on campus, but, it has been reported to be a facility most vulnerable to crime. However, almost no study has been conducted on crime in the library, which implies a need for research on the subject. The purpose of this study is specifically twofold. First, this study will suggest components of environmental plan to prevent fear over library crime on campus. Second, the study seeks to reveal the correlation between use per library space and fear of crime. This has been analyzed by conducting a survey among current university students, and the survey includes the following three details: first, fear over day/night crime per library space; second, components of environmental plan to prevent fear over crime per library space; third, level of use per library space on campus. The results of study show that fear of crime has low relation with crime occurrence, fear per library space is higher during the night than during the day, and the space where the fear level is usually high is the service facility. There is a difference for each space in terms of important components of environmental plan to prevent crime per library space, and installation of security device is most important. One must consider a plan for a crime safe environment regarding library space where the level of use during the day is low.

• Architectural research
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• v.24 no.1
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• pp.1-11
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• 2022

As the occurrence of a crime is dependent on different factors, their correlations are beyond the ordinary cognitive range. Owing to this limitation, systems face difficulty in correlating various factors, thereby requiring the assistance of artificial intelligence (AI) to overcome such limitations. Therefore, AI has become indispensable for crime prediction. Crimes can cause severe and irrevocable damage to a society. Recently, big data has been introduced for developing highly accurate models for crime prediction. Prediction of night crimes should be given significant consideration, because crimes primarily occur during nights, when the spatiotemporal characteristics become vulnerable to crimes. Many environmental factors that influence crime rate are applied for crime prediction, and their influence on crime rate may differ based on temporal characteristics and the nature of crime. This study aims to identify the environmental factors that influence sex and theft crimes occurring at night and proposes an artificial neural network (ANN) model to predict sex and theft crimes at night in random areas. The crime data of A district in Seoul for 12 years (2004-2015) was used, and environmental factors that influence sex and theft crimes were derived through multiple regression analysis. Two types of crime prediction models were developed: Type A using all environmental factors as input data; Type B with only the significant factors (obtained from regression analysis) as input data. The Type B model exhibited a greater accuracy than Type A, by 3.26 and 9.47 % higher for theft and sex crimes, respectively.