Advancements in Crowd Behavior Recognition Using Computer Vision Techniques for Enhanced Public Safety

Abstract

In recent decades, rapid urbanization and increased frequency of large-scale events have heightened the need for efficient and effective crowd management systems. Traditional monitoring solutions, which depend heavily on human operators, struggle to deliver timely responses to emergency situations in crowded environments. This article explores advanced methodologies in computer vision and artificial intelligence that automatically recognize crowd behavior, detect anomalies, and ensure rapid intervention, thereby significantly improving public safety management.