Title :
Real-Time Crowd Massing Risk Supervision System Based on Massing Crowd Counting in Public Venue
Author :
Sun Aijun ; Liu Mao ; Li Jianfeng
Author_Institution :
Coll. of Environ. Sci. & Eng., Nankai Univ., Tianjin, China
Abstract :
In this article, based on the FIST model, it proposes four parameters to describe the crowd massing risk in public venues that are the density (D), mutual interaction between each others (I), the personnel characteristics (C) and the impact derived form environmental (E) disturbance on the massing crowd. Then, it carries out the corresponding technical analysis for the four predefined parameters. First, it uses the crowd monitoring systems to estimate the crowd density on the spot; Second, the value of crowd pressure will be obtained through the pressure measurement network which describes the mutual affects between different persons; Third, it has neglected the influence of individual differences on the crowd as a whole; Fourth, it attributes all the influence factors to an index Integrated Disturbance Intensity, then establishes the corresponding mathematical model to quantify its intensity. Finally, it builds up the DICE model as the quantification of crowd massing risk.
Keywords :
accident prevention; public administration; risk analysis; FIST model; crowd monitoring systems; integrated disturbance intensity; massing crowd counting; pressure measurement network; public venue; real-time crowd massing risk supervision system; Educational institutions; Image storage; Mathematical model; Monitoring; Motion analysis; Personnel; Pressure measurement; Real time systems; Risk management; Sun;
Conference_Titel :
Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5272-9
DOI :
10.1109/CNMT.2009.5374743