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A risk probability-map generation model on multimedia services environment

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Abstract

The rapid growth of modern society has been a double-edged sword; it has led to positive results such as income growth due to the diversification of our society, but also negative results such as an increase in crime. For this reason, cities are confronting a wide range of issues. Social issues, especially criminal offenses, stir up more fear of crime among residents. The rapid societal penetration of digital devices such as smart phones, along with an increase in IT knowledge, has made our lives more convenient. However, cyber-crime and violent crime taking advantage of these benefits are also increasing. There is an increasing need for crime prevention and crime prediction in order to solve these problems, and many studies on crime are under way as part of our effort to respond to various changes in our society using a variety of prediction tools. Thus, in this study, a combined risk probability map generation model was suggested by predicting crime frequency through a Markov Chain Analysis, quantifying risks through objective classification of urban spaces and applying attribute-specific risk indexes and interpretation keys across the entire scope of the study. The crime prediction model based on risk probability map suggested in this study facilitates multimedia services using mobile devices such as smartphones and thus can be used to optimally plan patrol routes of police officers in zones vulnerable to crimes as well as placement of surveillance systems, which will in turn contribute to relieving many citizens’ anxiety about crime. Our model’s approach is too small environment in this research time. But we will try to more experiment environment is big such as town and state next research time.

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The authors have no conflict of interests related to the conduct and reporting of this research.

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Correspondence to Jin-Mook Kim.

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Kim, DH., Kim, JM., Jeong, YS. et al. A risk probability-map generation model on multimedia services environment. Multimed Tools Appl 75, 15709–15727 (2016). https://doi.org/10.1007/s11042-014-2441-0

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  • DOI: https://doi.org/10.1007/s11042-014-2441-0

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