crowd-detection

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

This project implements real-time crowd detection using YOLOv8. It identifies and tracks people in a video feed, detects crowd formation based on proximity, and logs the results in a CSV file.

Real-time crowd detection using TensorFlow.js and machine learning

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

Computer vision system that detects and spatially clusters groups of people in static images using a custom-trained Haar Cascade classifier and a Winner-Takes-All network implemented from scratch in MATLAB. Academic project from my Neuro-Fuzzy Systems course at UPIITA–IPN (2023).

An AI-based Smart Crowd Management System that detects and monitors crowd density in real-time using YOLOv8, OpenCV, Machine Learning, and Streamlit. The system supports live webcam, image, and video detection with heatmap visualization and overcrowding alerts for efficient crowd monitoring and public safety.

Intelligent crowd monitoring system combining YOLO-based people detection with a MERN architecture to analyze crowd density and provide real-time monitoring through an interactive dashboard.

Real-time crowd detection and analytics system using YOLOv8, PyQt5, OpenCV, and custom object tracking.

Person detection and density analysis using YOLOv8. Evolution of CrowdCluster.

A real-time computer vision system for monitoring and analyzing crowd density using YOLO-based object detection and tracking.

Real-time crowd panic detection system using YOLOv8 and OpenCV. Detects abnormal crowd behavior, estimates density, triggers alarms, and logs events via a live Flask dashboard. Supports webcam, video file, and RTSP streams.

AI-powered smart city crowd management and dynamic bus dispatch system using CSRNet density map regression to monitor transit stop overcrowding and optimize public transportation.

라즈베리파이 + YOLOv8으로 실내 혼잡도를 감지하고 웹 대시보드로 실시간 시각화하는 AIoT 시스템

Crowd detection system powered by YOLOv8 and OpenCV. Features modular architecture, video processing pipeline, and detailed performance analysis for urban environments.

Deep learning system for crowd density detection and behavioural anomaly detection using YOLOv8 and CNN-LSTM, with a Flask monitoring dashboard.

MandirGo is an AI-based Smart Temple Crowd & Pilgrimage Management System leveraging Computer Vision, real-time analytics, and intelligent booking to enhance safety, optimize crowd flow, and seamless pilgrimage experience.

Offline CrowdAware system for Raspberry Pi 4B and Heltec LoRa V3 using Raspberry Pi Camera Module 3 and MLX90640 Thermal Camera.

Crowd detection system for YIC 2023

Final Project for [CS-1390] IML 👀

A real-time crowd detection system built with TypeScript that analyzes webcam/video input to detect and count people, estimating crowd density for smart surveillance and safety monitoring