Early-warning analysis of crowd stampede in metro station commercial area based on internet of things
作者： Kefan Xie , Yanlan Mei , Ping Gui , Yang Liu
DOI: 10.1007/S11042-018-6982-5
关键词:
摘要: Crowd stampede has attracted significant attention of emergency management researchers in recent years. Early-warning crowd metro station commercial area is discussed this paper under the context Internet Things (IoT). Metro one entity carriers E-commerce. IOT a new concept realizing intelligent sense, monitoring, tracking and management, which can be used early-warning analysis station. Stampede risk plays an important role ensuring operation e-commerce online. Firstly, laws characteristics movement are studied, include laeuna effect, block effect aggravation effect. Secondly, paradigm constructed from four dimensions, ie. function, modules, principle process. And then, environment, AHPsort II applied to integrate information classify level. Finally, takes Wuhan A as example verify practicability effectiveness application area.
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