Enhancing Crowd Safety Resilience Through Systematic Analysis

Crowd safety has become an increasingly critical concern in contemporary society due to the convergence of various domains such as sports, entertainment, politics, and more. Consequently, it is imperative to prioritize a systematic and robust approach to safety and reliability analysis. The primary objective of crowd safety is to safeguard the health and well-being of all stakeholders, including patrons, event organizers, safety and security officers, and others. By conceptualizing crowd safety as a performance functionality inherent within the system they are part of, the concept of resilience emerges as a pivotal feature that can be seamlessly integrated into crowd safety management. This perspective views the resilience of a crowd as determined by evaluating four key characteristics: disruption, adaptation, absorption, and restoration. Additionally, it can evolve and improve over time through continuous learning. To assess the resilience of a crowd, this book chapter introduces the concept of Bayesian networks as a valuable tool for analysis. It then demonstrates how Bayesian networks can be effectively integrated to examine and enhance the resilience of crowd safety. This holistic approach ensures that crowd safety remains adaptable and responsive in the face of evolving challenges, ultimately contributing to all involved's overall well-being and security.