多维特征可视化在场馆应急管理中的应用

Wenyan Yan, Degang Yang
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引用次数: 0

摘要

在“互联网+”的大背景下,利用先进的信息技术和物联网技术打造全新的“智慧场馆”已成为当前的主要趋势。然而,由于场馆人数众多,人员类型复杂,突发事件频发,对场馆进行智能化管理是一项具有挑战性的任务。介绍了一种多维特征融合轨迹聚类算法,并设计了可视化分析系统。该系统可以实时监控场馆人员的运动轨迹,分析人员类型,挖掘人员的运动规律,及时发现异常情况,预防和处理突发事件,很好地满足了“智慧场馆”的需求。与现有的轨迹聚类方法相比,该聚类算法逻辑更紧密,聚类内容更丰富,更具现实价值,为场馆应急管理提供了强有力的技术支持。
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Application of Multidimensional Feature Visualization in Emergency Management of Venues
In the background of “Internet+”, the use of advanced information technology and Internet of Things technology to create brand-new “smart venues” has become the main trend now. However, due to the large number of people, complex personnel types and frequent emergencies, it is a challenging task to manage the venue intelligently. This paper introduces a multidimensional feature fusion trajectory clustering algorithm, and designs a visual analysis system. The system can monitor the movement track of the venue personnel in real time, analyze the type of personnel, dig the movement rule of personnel, find abnormal situations in time, prevent and deal with emergencies, and well meet the demand of “smart venue”. By contrast with the existing trajectory clustering methods, the clustering algorithm logic more closely, clustering richer, more realistic value, provides strong technical support for emergency management of venues.
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