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From the 2015 Hajj tragedy to daily rush-hour congestion, crowd disasters often stem from one issue: lack of real-time visibility. This article explains how AI-powered crowd density monitoring helps cities detect high-risk congestion, prevent emergencies, and manage public spaces safely—without tracking individuals.

AI-powered crowd density monitoring is transforming how transport hubs and public spaces are managed in France. This article explores how GDPR-compliant Edge AI solutions are replacing beacon-based tracking systems, and how privacy-by-design technologies enable accurate, anonymized pedestrian analytics in high-density environments.

Modern train and metro stations in France require more than basic passenger counting. By combining computer vision, edge AI, and real-time analytics, passenger flow monitoring systems provide instant visibility into crowd density, congestion risks, and movement patterns—supporting safer operations, optimized station layouts, and long-term smart mobility planning.

Traditional crowd monitoring tools can no longer handle the complexity of modern transport hubs. This article explores how AI-powered computer vision and Edge AI enable real-time crowd congestion detection in metro and train stations—improving passenger safety while staying privacy-first and GDPR-compliant across Europe.