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Safe Route Recommendation Method to Prevent Crime Exposure

机译:安全路线推荐方法,以防止犯罪曝光

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In modern society, various crimes are occurring. This is seriously threatening the safety of the city. It is most important to prevent crime before it occurs. There are many studies to prevent crime. However, most of the existing research methods try to prevent crime by analyzing thefrequency of crime occurrence and the motives of crime using statistical and psychological factors. Several recent studies have used Big Data to provide real-time crime incidence rates to mobile phone users in specific regions. However, there is no research that reports the risk of crime accordingto the time and day of the user’s movement. In this paper, we propose a safety route recommendation method according to user’s movement time and day of the week. To do this, we calculate the crime risk rate for a particular facility and calculate the crime risk rate for the routebased on the crime risk rate of the facilities included in the user’s route. To calculate the facility crime risk rate, we analyze information on the facility where the crime occurred for the five major types of crime. The facility crime risk rate is expressed in levels from 1 to 10,with 1 being the safest and 10 being the most dangerous. An analysis of crime information shows that the probability of crime on the route increases when facilities with high crime risk or facilities with similar crime rates are in close proximity. Even at the same facility, crime is 20% morelikely to occur at night than night, and more crimes occur on Fridays, Saturdays and Sundays than other days. Therefore, the crime risk rate for the route is calculated by using the risk rate of the crime occurrence of the facilities included in the route, the risk rate of crime occurrenceat the adjacent facilities, and the time and day weight. When a user chooses a start and end points, our system calculates the crime risk rate according to the time and day of use and recommends the safest route among various routes.
机译:在现代社会中,发生了各种罪行。这严重威胁着城市的安全。在发生之前预防犯罪是最重要的。有很多研究可以防止犯罪。然而,大多数现有的研究方法通过分析犯罪事件的频繁和使用统计和心理因素的犯罪动机来预防犯罪。最近的几项研究已经使用大数据来为特定地区的手机用户提供实时犯罪发病率。但是,没有关于用户运动的时间和日期的犯罪风险的研究。在本文中,我们提出了一种根据用户的运动时间和一周中的安全路由推荐方法。为此,我们计算特定设施的犯罪风险率,并计算出于用户路线所包含的设施犯罪率的犯罪风险率。为了计算设施犯罪率风险率,我们分析了关于犯罪发生的犯罪的设施的信息。设施犯罪率风险率在1到10的级别表示,最安全,10个是最危险的。犯罪信息分析表明,当犯罪风险或犯罪率相比具有相似犯罪率的设施的设施密切关注时,犯罪的可能性增加。即使在同一设施,犯罪率也可能发生在晚上比夜晚更加不变,而且周五,周六和周日的犯罪比其他日子更多。因此,通过使用路线中包含的设施的犯罪率的风险率,犯罪的风险率以及额外设施的风险率以及时间和日重量来计算犯罪率。当用户选择开始和结束点时,我们的系统根据使用的时间和日期计算犯罪风险率,并建议在各种路线之间最安全的路线。

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