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A risk probability-map generation model on multimedia services environment

机译:多媒体服务环境下的风险概率图生成模型

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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.
机译:现代社会的飞速发展是一把双刃剑。它带来了积极的结果,例如由于我们的社会多样化导致的收入增长,也带来了消极的结果,例如犯罪增加。因此,城市面临着各种各样的问题。社会问题,尤其是刑事犯罪,加剧了居民对犯罪的恐惧。数字设备(如智能手机)在社会中的快速普及以及IT知识的增加,使我们的生活更加便捷。但是,利用这些好处的网络犯罪和暴力犯罪也在增加。为了解决这些问题,对预防犯罪和犯罪预测的需求日益增长,作为我们使用各种预测工具应对社会各种变化的努力的一部分,正在进行许多犯罪研究。因此,在这项研究中,提出了一种组合的风险概率图生成模型,该模型通过马尔可夫链分析法预测犯罪发生频率,通过对城市空间进行客观分类来量化风险,并在整个研究过程中应用特定于属性的风险指数和解释键。这项研究中提出的基于风险概率图的犯罪预测模型可以促进使用智能手机等移动设备的多媒体服务,因此可以用来优化规划易受犯罪影响地区警务人员的巡逻路线以及监视系统的位置,反过来又有助于减轻许多公民对犯罪的忧虑。我们的模型方法在此研究时间内环境太小。但是下一次研究时间我们将尝试更多的实验环境如城镇和州大。

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