International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 3 (May-June 2025) Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

A Novel Approach to Crowd Management Using Machine Learning

Author(s) Mr. Surya Narayanan, Jayakrishnan A, Jithin K C, Reni Jose
Country India
Abstract Crowd Management Systems (CMS) leverage artificial intelligence (AI) to enhance public safety by organizing and monitoring crowd dynamics in various settings. This study examines AI-based tools—machine learning, computer vision, and real-time data processing—used to predict crowd behavior and manage risks effectively. CMS utilizes predictive models and video analytics to autonomously monitor crowd density, detect potential hazards, and enable prompt emergency responses across domains such as stadiums, airports, and smart city infrastructure. By analyzing extensive streams of video and sensor data, CMS improves response accuracy and optimizes resource allocation. As a component of smart city initiatives, CMS integrates data from multiple sources, such as transit and emergency services, continuously refining its efficiency. AI-powered CMS systems are critical for safe, efficient crowd management, with applications in event automation, congestion control, and rapid evacuation planning in high-traffic public spaces.
Keywords Crowd management, AI, Machine Learning
Field Engineering
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-05-04
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.43784
Short DOI https://doi.org/g9hsgz

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