监视可识别人群的框架

Sheikh Nasir Saeed, A. Abid, Ehsan U. Waraich, S. Atta, A. Naseer, A. Sheikh, Emad A. Felemban
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引用次数: 5

摘要

如今,管理大型拥挤的活动是一项非常具有挑战性的任务。人们正在寻找能够轻松监控人群、追踪个体、研究人群形成和变形模式的解决方案。每年农历的第12个月,来自世界各地的数百万穆斯林聚集在沙特阿拉伯的麦加进行朝觐。在朝觐期间监视人群是一项巨大的挑战。在本文中,我们提出了一个可识别的人群监测框架,名为iccrowd。该框架收集、识别、推断、分析、存储和检索每个预注册参与者(朝圣者)的实时位置信息,并提供近乎实时的人群数字视图。iccrowd框架采用三层设计方法,即设备层、中间件层和应用层。我们在朝觐事件的背景下用模拟数据证明了我们提出的框架。
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iCrowd — A framework for monitoring of identifiable crowd
To manage large crowded events is a very challenging task nowadays. People are looking for solutions in which they can easily monitor the crowd, trace individuals, study formation and deformation patterns of the crowd. Millions of Muslims from around the world gather and perform Hajj in Makkah, Saudi Arabia in the 12th month of every lunar year. To monitor the crowd during Hajj is a great challenge. In this paper, we are proposing an identifiable crowd monitoring framework named iCrowd. This framework collect, identify, infer, analyze, store and retrieve the real-time location information of each of the pre-registered participants (pilgrims), and provides a digital view of crowd in near real-time. iCrowd framework is designed on a three-layer approach, device layer, middleware layer, and the application layer. We demonstrate our proposed framework with simulated data in the context of the event of Hajj.
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