WIT Press


Crowd Management Using Fuzzy Logic And G.I.S.

Price

Free (open access)

Paper DOI

10.2495/RISK100281

Volume

43

Pages

10

Page Range

325 - 334

Published

2010

Size

1379 kb

Author(s)

N. P. Deshpande & R. Gupta

Abstract

Crowd management using fuzzy logic and GIS N. P. Deshpande & R. Gupta Civil Engineering Department, BITS Pilani, India 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 GIS 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 GIS 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. Keywords: crowd management, crowd density, movement detection, image processing, use of fuzzy logic, GIS application.

Keywords

crowd management, crowd density, movement detection, imageprocessing, use of fuzzy logic, G.I.S. application