Essentials of an Integrated Crowd Management Support System Based on Collective Artificial Intelligence
Giuseppe Vizzari, Stefania Bandini

TL;DR
This paper presents an integrated crowd management system leveraging collective artificial intelligence to simulate, analyze, and influence pedestrian behavior in real-time, enhancing security and operational decision-making.
Contribution
It introduces a comprehensive framework combining sensors, software tools, and AI-driven simulation for real-time crowd management and decision support.
Findings
Supports real-time crowd behavior analysis
Enables dynamic environmental control and communication
Improves decision-making efficiency in crowd management
Abstract
The simulation of the dynamical behavior of pedestrians and crowds in spatial structures is a consolidated research and application context that still presents challenges for researchers in different fields and disciplines. Despite currently available commercial systems for this kind of simulation are growingly employed by designers and planners for the evaluation of alternative solutions, this class of systems is generally not integrated with existing monitoring and control infrastructures, usually employed by crowd managers and field operators for security reasons. This paper introduces the essentials and the related computational frame- work of an Integrated Crowd Management Support System based on a Collective Artificial Intelligence approach encompassing (i) interfaces from and to monitored and controlled environments (respectively, sen- sors and actuators), (ii) a set of software…
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Taxonomy
TopicsEvacuation and Crowd Dynamics · Video Surveillance and Tracking Methods · Traffic control and management
