Use computer vision to detect vehicle density and optimize signal timing using reinforcement learning.

AI Traffic Manager An AI-powered traffic management system that uses YOLOv8 for real-time vehicle detection and machine learning models to predict traffic density and suggest optimized green light durations. The system is designed for smart city traffic control to reduce congestion, improve flow, and enhance road safety.

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Smart Traffic Control System - AI-powered traffic light optimization with console interface and SFML graphical simulation

Smart Traffic Light Monitoring System with AI-powered vehicle detection and adaptive signal control

AI-powered traffic light system that creates real-time green corridors for ambulances using GPS tracking and smart signal control.

AI-Powered Smart Traffic Light System — Dynamic traffic control using YOLOv8, ByteTrack, and smart zone-based logic. Real-time vehicle detection, tracking, and adaptive light timing with a Pygame intersection simulation

AI-powered smart traffic light system using Python + YOLOv8 + Arduino. Detects vehicle density via webcam and dynamically controls LEDs for a toy traffic model.

“Smart & Adaptive Traffic Light Control System” The project focuses on building an AI-powered adaptive traffic light system that analyzes density, jam levels, peak hours, and emergency vehicle priority to optimize signal timing in real time.

Smart_Light_AI is an AI-powered smart traffic management system using YOLOv8 for real-time vehicle detection and adaptive signal control. It dynamically optimizes traffic signals and prioritizes emergency vehicles. Built with FastAPI backend and React-based Admin & Public dashboards.

Smart AI-Based Traffic Light and Health Monitoring System This project is an advanced AI and IoT-powered traffic light system that not only controls vehicle flow but also integrates computer vision (OpenCV, YOLO) and AI/ML algorithms for intelligent decision-making. Additionally, it has applications in health and emergency response systems.