A Review of Deep Learning Techniques for Crowd Management

Abstract

Crowd Management is extremely important for maintaining safety and order in areas, such as events, transportation hubs, and urban centers. In the years deep learning methods have become tools for dealing with the complexities associated with crowd management. The adoption of this technology represents a change in how we analyze, predict, and respond to crowd dynamics. Deep learning algorithms can process amounts of data using CNNs. Learn intricate patterns enabling the creation of advanced models that can anticipate crowd behavior, identify unusual occurrences, and optimize crowd flow. By utilizing information from surveillance cameras, social media platforms, and other sources these models can provide real-time insights that empower authorities to make decisions and take measures to ensure public safety. To sum up, integrating deep learning techniques into crowd management offers a path toward improving situational awareness and effectively addressing the challenges presented by large gatherings of people. Further research and application of these technologies have the potential for enhancing crowd.