DIAS CHRIS FRANCOMEVIN QUADROSSAHEEL SHAIKHSAIESHWAR MALKARNEKARYASH SATISH BHANDARI2026-05-272026-05-272026http://rcca.ndl.gov.in/handle/123456789/626Crowd crushes and stampedes are tragic yet preventable incidents. The tragedy during the RCB celebration at M. Chinnaswamy Stadium highlighted the consequences of inadequate crowd monitoring. Smart Crowd Detection and Management System is designed to address this issue through an AI- powered, real-time surveillance system. The system uses a Raspberry Pi 5 integrated with a camera module to run two AI models: YOLOv11n for crowd counting and density estimation, and YOLOv8 Pose for fall detection. When abnormal conditions such as overcrowding or falls are detected, the system instantly alerts security personnel through a Flutter-based mobile application. Alerts include geolocation data via Google Maps and automated voice calls using Twilio. The solution is real-time, cost-effective, scalable, and suitable for deployment in public venues such as stadiums, railway stations, malls, and festivals.enOther