Toward an Integrated Intelligent Framework for Crowd Control and Management (IICCM)

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Abstract
Managing large-scale gatherings, such as global festivals, sporting events, and religious congregations, presents substantial challenges in ensuring crowd safety and control. Innovative frameworks are essential to address these complexities effectively. The Integrated Intelligent Crowd Control and Management (IICCM) framework combines cutting-edge technologies, including Computer Vision (CV), Artificial Intelligence (AI), and the Internet of Things (IoT), to enhance participant safety and optimize crowd management. CV enables precise real time identification and tracking, AI analyzes crowd behavior to anticipate risks, and IoT gathers environmental data to improve crowd flow, alleviate congestion, and provide timely assistance. Additionally, the framework facilitates emergency evacuation planning by modeling crowd dynamics and identifying safe, efficient escape routes. Although suitable for diverse events, the Hajj pilgrimage—a uniquely large and dynamic annual gathering—provides a rigorous test case for the IICCM framework. Managing millions of participants from varied cultural and linguistic backgrounds highlights the system’s adaptability and robustness. By effectively addressing Hajj specific challenges, the IICCM framework demonstrates its scalability and applicability to other large-scale events. This research offers valuable insights for decision-makers seeking to implement advanced crowd management technologies.

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