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

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 M...

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Main Authors: Tarik Alafif, Mohammad Jassas, Alaa E. Abdel-Hakim, Ghada Alfattni, Hassan Althobaiti, Mohammed Ikram, Amirah Alharbi, Hussam Alsharif, Mazin AlShamrani, Ebtisam Alharbi, Tahani Alsubait, Abdullah Alhawsawi, Badr Alsolami, Khalid Khayyat
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10942376/
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author Tarik Alafif
Mohammad Jassas
Alaa E. Abdel-Hakim
Ghada Alfattni
Hassan Althobaiti
Mohammed Ikram
Amirah Alharbi
Hussam Alsharif
Mazin AlShamrani
Ebtisam Alharbi
Tahani Alsubait
Abdullah Alhawsawi
Badr Alsolami
Khalid Khayyat
author_facet Tarik Alafif
Mohammad Jassas
Alaa E. Abdel-Hakim
Ghada Alfattni
Hassan Althobaiti
Mohammed Ikram
Amirah Alharbi
Hussam Alsharif
Mazin AlShamrani
Ebtisam Alharbi
Tahani Alsubait
Abdullah Alhawsawi
Badr Alsolami
Khalid Khayyat
author_sort Tarik Alafif
collection DOAJ
description 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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spelling doaj-art-6ed723302cf04cdcaf919e1a692a01822025-08-20T02:26:15ZengIEEEIEEE Access2169-35362025-01-0113585595857510.1109/ACCESS.2025.355515410942376Toward an Integrated Intelligent Framework for Crowd Control and Management (IICCM)Tarik Alafif0https://orcid.org/0000-0003-1443-446XMohammad Jassas1https://orcid.org/0000-0002-6238-7808Alaa E. Abdel-Hakim2https://orcid.org/0000-0002-0003-6914Ghada Alfattni3https://orcid.org/0000-0002-2060-195XHassan Althobaiti4https://orcid.org/0000-0001-9018-2706Mohammed Ikram5https://orcid.org/0000-0001-5111-9923Amirah Alharbi6https://orcid.org/0000-0002-7449-0642Hussam Alsharif7https://orcid.org/0009-0002-2474-842XMazin AlShamrani8https://orcid.org/0000-0002-8706-0879Ebtisam Alharbi9https://orcid.org/0000-0002-3887-3857Tahani Alsubait10https://orcid.org/0000-0001-5117-5108Abdullah Alhawsawi11https://orcid.org/0000-0001-7551-8806Badr Alsolami12https://orcid.org/0000-0002-3035-7268Khalid Khayyat13https://orcid.org/0000-0003-3175-0747Department of Computer Science, Jamoum University College, Umm Al-Qura University, Al Jumum, Saudi ArabiaDepartment of Computer Science, Jamoum University College, Umm Al-Qura University, Al Jumum, Saudi ArabiaDepartment of Computer Science, Jamoum University College, Umm Al-Qura University, Al Jumum, Saudi ArabiaDepartment of Computer Science, Jamoum University College, Umm Al-Qura University, Al Jumum, Saudi ArabiaDepartment of Computer Science, Jamoum University College, Umm Al-Qura University, Al Jumum, Saudi ArabiaDepartment of Computer Science, Jamoum University College, Umm Al-Qura University, Al Jumum, Saudi ArabiaDepartment of Data Science, Umm Al-Qura University, Makkah, Saudi ArabiaDepartment of Computer Science, Jamoum University College, Umm Al-Qura University, Al Jumum, Saudi ArabiaHajj and Umrah Research Institute, Umm Al-Qura University, Makkah, Saudi ArabiaDepartment of Data Science, Umm Al-Qura University, Makkah, Saudi ArabiaDepartment of Computer Science and Artificial Intelligence, Umm Al-Qura University, Makkah, Saudi ArabiaHajj and Umrah Research Institute, Umm Al-Qura University, Makkah, Saudi ArabiaDepartment of Islamic Architecture, Umm Al-Qura University, Makkah, Saudi ArabiaDepartment of Computer and Network Engineering, Umm Al-Qura University, Makkah, Saudi ArabiaManaging 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.https://ieeexplore.ieee.org/document/10942376/Crowd managementlarge-scale gatheringsartificial intelligencecomputer visionInternet of Thingsemergency evacuation
spellingShingle Tarik Alafif
Mohammad Jassas
Alaa E. Abdel-Hakim
Ghada Alfattni
Hassan Althobaiti
Mohammed Ikram
Amirah Alharbi
Hussam Alsharif
Mazin AlShamrani
Ebtisam Alharbi
Tahani Alsubait
Abdullah Alhawsawi
Badr Alsolami
Khalid Khayyat
Toward an Integrated Intelligent Framework for Crowd Control and Management (IICCM)
IEEE Access
Crowd management
large-scale gatherings
artificial intelligence
computer vision
Internet of Things
emergency evacuation
title Toward an Integrated Intelligent Framework for Crowd Control and Management (IICCM)
title_full Toward an Integrated Intelligent Framework for Crowd Control and Management (IICCM)
title_fullStr Toward an Integrated Intelligent Framework for Crowd Control and Management (IICCM)
title_full_unstemmed Toward an Integrated Intelligent Framework for Crowd Control and Management (IICCM)
title_short Toward an Integrated Intelligent Framework for Crowd Control and Management (IICCM)
title_sort toward an integrated intelligent framework for crowd control and management iiccm
topic Crowd management
large-scale gatherings
artificial intelligence
computer vision
Internet of Things
emergency evacuation
url https://ieeexplore.ieee.org/document/10942376/
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