Crowd management using fuzzy logic and G.I.S.

Abstract

Our main objective is to design a computer based system to monitor the crowding system so as to avoid crowding disasters.We have proposed a two-step mode. The first step is 'pre-disaster planning' including determination of sensitive locations and space management, evacuation paths using G.I.S. and management related arrangements. The second step is real time analysis of crowds to detect a possible emergency. It contains two modules, the first being a method to determine crowding situations and plan of action, and the second being the determination of the shortest evacuation path for the current area under surveillance. In the fuzzy inference system, used in determining crowding situation, crowd density is determined with the help of a number of pixels and shape of objects. For determining speed and cumulative displacement a new method is named 'determination of speed and displacement from images with help of object characterization'. The shortest path is determined with the help of G.I.S. and the overall crowding situation. We have considered two case studies:1. Open air theatre: this particular case study was considered to get better understanding of general crowd movement patterns in the absence of crowd management systems and possible sensitive locations. 2. Auditorium: this case study was used to check the applicability of the overall project and to determine an evacuation path network. While applying this case study we checked for results such as accuracy and usability of components of the project such as crowd density determination, fuzzy inference system, Determination of speed and displacement etc., and overall usability.

Human Stampedes: An Updated Review of Current Literature

“…A challenge commonly reported was the conception of venue designs that are optimal in case of emergencies, but also practical in normal situations 38 47 , 57 Avoiding bottlenecks and intersection or merging flows was widely recommended, as well as removing obstacles and protecting emergency lanes 43 .…”