AI-Powered Drowsiness Detection System | Python, OpenCV, MediaPipe & Dlib | Final Year Project
🚗 Hybrid Drowsiness Detection System
This project is an AI-powered driver monitoring system designed to detect driver drowsiness in real time and help prevent road accidents. The system combines the capabilities of MediaPipe and Dlib facial landmark detection to accurately monitor eye movements and detect signs of fatigue.
Source Code: https://github.com/KAMRAN16-byte/AI-D...
🔹 Features
✔ Real-time face and eye detection
✔ Eye Aspect Ratio (EAR) calculation
✔ Driver calibration process using MediaPipe
✔ Drowsiness detection using Dlib facial landmarks
✔ Audio alert system for driver warning
✔ Live web dashboard for monitoring
✔ User authentication and management
✔ Event logging and alert history
🛠 Technologies Used
Python
OpenCV
MediaPipe
Dlib
Flask
SQLite
HTML, CSS, JavaScript
Bootstrap
📌 Project Workflow
User Login
Driver Calibration
Real-Time Monitoring
Drowsiness Detection
Alert Generation
Dashboard Monitoring
🎯 Objective
The primary goal of this project is to improve road safety by detecting driver fatigue at an early stage and providing immediate alerts to reduce the risk of accidents.
#Python #OpenCV #ArtificialIntelligence #ComputerVision #MediaPipe #Dlib #Flask #DriverMonitoring #DrowsinessDetection #FinalYearProject #CSEProject #MachineLearning #AIProject