The proposed solution leverages AI-driven video feed analysis from existing camera networks, such as those in Times Square, to provide real-time crowd density monitoring for large-scale public events. The system generates dynamic heatmaps that visualize crowd density and movement patterns by integrating YOLO (You Only Look Once) and TensorFlow models. The camera feeds directly into ATAK via a plugin, allowing event organizers and public safety agencies to see continuous, actionable insights via heatmaps for proactive crowd management. The solution enables timely adjustments in resource deployment, helping to prevent overcrowding and enhance overall safety. Designed to scale and adapt across varied event settings, this approach ensures swift situational awareness, enabling improved decision-making and coordination. This innovative system significantly advances traditional static monitoring methods by providing a responsive, AI-powered tool for safer, more efficient public event management.