CrowdVision is an advanced real-time crowd monitoring system that utilizes AI and Computer Vision to ensure public safety by detecting and analyzing crowd density through live video feeds. The system uses YOLOv8 deep learning technology to identify individuals, classify crowd levels, and trigger alerts during high-density situations. Key Highlights: ➥ Real-Time Crowd Detection using YOLOv8 and OpenCV with 95%+ accuracy ➥ Zone-Based Density Analysis with dynamic Low, Medium, High, and Critical classifications ➥ Secure Authentication System with user registration, login, and session management ➥ Interactive Web Dashboard for live monitoring, analytics, and alert history tracking ➥ Responsive Design with smooth UI/UX for desktop and mobile platforms Tech Stack: Python, Flask, YOLOv8, OpenCV, SQLite, HTML, CSS, JavaScript This project allowed me to integrate AI, Deep Learning, and Web Development to build a real-time safety monitoring solution with intelligent analytics and professional design.