Volume 2 - Issue 1, January - February 2026

Crowd safety management has become a major concern during large public gatherings such as festivals, concerts, and events. Traditional monitoring systems rely on manual surveillance, which is time-consuming and prone to human error. This paper presents “Crowd Sense,” an AI-based intelligent crowd monitoring system designed to improve public safety. The proposed system uses deep learning techniques such as object detection, density estimation, and movement analysis to monitor crowd behavior in real time. It can detect overcrowding, abnormal movement patterns, and potential risks, and generate automated alerts for authorities. Experimental results show that the system achieves high accuracy and reliability compared to traditional methods. The proposed solution provides an efficient, proactive, and data-driven approach for safer event management.

P.JayaLakshmi, J.Prasanna, M.Rakesh, Sk.Shahid,Y.Swapna Madhuri,"Crowd Sense: An AI-Based Intelligent Crowd Monitoring System for Public Safety (Real-Time Detection, Density Estimation, and Risk Prediction Using Deep Learning)" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(1): Page(963-966) Jan-Feb 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.