Introduction

Stampede is a computer vision system designed to monitor crowd density in public spaces and provide real-time alerts for potential dangerous crowding situations. Using object detection, density mapping, and a user-friendly dashboard, this system helps safety officials prevent dangerous situations before they occur.

🎯 Core Features

• People Detection: Accurate identification of individuals in crowded scenes using YOLOv8
• Density Mapping: Visual representation of crowd distribution with color-coded risk zones
• Real-time Alerts: Immediate notifications when crowd density exceeds safe thresholds
• Analytics Dashboard: User-friendly interface to monitor multiple locations simultaneously

🔍 Use Cases

• Religious Gatherings: Temples, pilgrimages, festivals
• Transport Hubs: Railway stations, bus terminals, airports
• Public Events: Concerts, political rallies, sports events
• Tourist Attractions: Museums, monuments, theme parks

💻 Technical Architecture

• Computer Vision: YOLOv8 for object detection, OpenCV for image processing
• Backend: Python with potential for FastAPI implementation
• Frontend: Streamlit dashboard for visualization and control
• Deployment: Cloud-based with potential for edge computing (Raspberry Pi)

✅ Task Board

Phase 1 – Detection Baseline (Week 1–2)