An Alert System: Using Fuzzy Logic for Controlling Crowd Movement by Detecting Critical Density Spots

When people form crowds without an orderly arrangement, we need to consider how to best control their movement to provide safety and maximize their experience. Controlling a large crowd is a complicated and costly operation, but it is important to prevent risky situations that can lead to trampling and crushing, and to provide general public safety. Crowd control forces must be able to organize people to provide successful crowd management. In this paper we examine two types of crowds: structured crowds, where people are heading towards the same goal and in generally the same direction, as happens in religious gatherings like the Islamic Hajj or the Hindu Kumbh Mela; and unstructured crowds, where people walk in different directions, as occurs in train stations and in the centers of towns and cities. By identifying the locations of each individual in a crowd, many potential problems of controlling crowds can be detected and avoided, since we will able to identify the direction and speed of each individual and compare it to the surrounding crowd. We propose an alert system as a way of keeping crowds safe in risky situations. The alert system focuses on scrutinizing the status of individuals in order to inform the authorities in case of risk behavior. Fuzzy logic is proposed as the basis for the alert system for deciding if the locations of individuals are considered critical spots causing obstruction of crowd motion. The aim of this paper is to establish a system that is able to process and analyze the individuals’ locations according to their current locations status. The system is using the fuzzy logic, as the machine starts to learn the critical density spots by pointing these locations.