In a previous research, the authors proposed a security information service, called Personalized Real-time Information with Security Map (PRISM), which personalizes the incident information based on living area of individual users. The purpose of this paper is to extend PRISM to conduct sophisticated analysis of street crimes. The extended features enable to look back on past incident information and perform statistical analysis.
To analyze street crimes around living area in more detail, the authors add three new features to PRISM: showing a past heat map, showing a heat map focused on specified type of incidents and showing statistics of incidents for every type. Using these features, the authors visualize the dynamic transition of street crimes in a specific area and the whole region within Kobe city. They also compare different districts by statistics of street crimes.
Dynamical visualization clarifies when, where and what kind of incident occurs frequently. Most incidents occurred along three train lines in Kobe city. Wild boars are only witnessed in a certain region. Statistics shows that the characteristics of street crimes is completely different depending on living area.
Previously, many studies have been conducted to clarify factors relevant to street crimes. However, these previous studies mainly focus on interesting regions as a whole, but do not consider individual’s living area. In this paper, the authors analyze street crimes according to users’ living area using personalized security information service PRISM.
This research was partially supported by the Japan Ministry of Education, Science, Sports, and Culture [Grant-in-Aid for Scientific Research (B) (16H02908, 15H02701), Grant-in-Aid for Scientific Research (A) (17H00731), Challenging Exploratory Research (15K12020)] and Tateishi Science and Technology Foundation (C) (No.2177004).
Kagawa, T., Saiki, S. and Nakamura, M. (2019), "Analyzing street crimes in Kobe city using PRISM", International Journal of Web Information Systems, Vol. 15 No. 2, pp. 183-200. https://doi.org/10.1108/IJWIS-04-2018-0032
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