crowd-monitoring

System integrated with YOLOv4 and Deep SORT for real-time crowd monitoring, then perform crowd analysis. The system is able to monitor for abnormal crowd activity, social distance violation and restricted entry. The other part of the system can then process crowd movement data into optical flow, heatmap and energy graph.

Experimental Python and FastAPI crowd-monitoring system for person detection, density analysis, risk scoring, and incident alerting

AI-powered multi-camera surveillance with posture classification, fall/inactivity detection, heatmaps, and real-time alerts. Built using OpenCV, MediaPipe, Streamlit & Flask.

Crowd monitoring and management using real-time data from IP camera and Laptop camera footage which aims to provide users with insights into the crowd density at various locations espicially at local market places , shops ,malls. This helps users make informed decisions about visiting places based on the level of crowdiness.

Face Recognition from Crowd by using yolov7 .Extracting the faces from a video/image/live source, which is then passed to the custom facenet network in order to recognize the peoples

A machine learning-based social distance estimation and crowd monitoring system for surveillance cameras

Crowd monitoring and cluster detection system with heatmap using Python & OpenCV

Full-stack web application for the visualization of road attributes and route planning in Amsterdam using area avoidance, focusing on the needs of the elderly and vulnerable people.

The Smart Queue Monitor is a real-time computer vision system that uses YOLOv8n and DeepSort to detect and track people in queue and service areas. It provides live analytics including queue length, waiting times, average service duration, and status alerts. With dynamic ROI adjustment, smooth tracking, and privacy features like face blurring

Scalable, privacy-aware crowd flow monitoring

AI-powered real-time crowd monitoring system using YOLOv8, OpenCV and Flask for overcrowding detection and safety alerts.

Local-first AI platform for real-time airport operations monitoring, combining edge computer vision, deterministic risk assessment, and an on-premise LLM.

Smart Crowd Panic & Suffocation Detection System using ESP32

SurakshaSetu is an AI-powered crowd safety and smart event management platform built for festivals, religious gatherings, and large public events. It provides real-time crowd density monitoring, live heatmaps, congestion alerts, intelligent route guidance, emergency response support, and analytics to help organizers and authorities prevent stampede

Computer vision-based CCTV person detection and crowd monitoring system using TensorFlow, OpenCV, and Streamlit.

Multi-agent crowd surveillance system for real-time safety monitoring at large events

AI-powered real-time crowd monitoring and disaster management platform using YOLOv8, FastAPI, React, and TypeScript.

Documentation repo for a computer vision digital twin prototype for airport passenger flow monitoring.

AI설계및실습. 코레일 역사 내 시설 혼잡도 분석 풀스텍

Real-time people counting and crowd monitoring using YOLO11 | AI-powered bidirectional tracking | Perfect for schools, retail, exhibitions | Raspberry Pi ready