🧠 Real-Time Attentiveness Monitoring System

A Python-based real-time system that monitors user attentiveness using facial landmark detection. Designed to detect drowsiness and inattention through eye tracking and yawning analysis, this tool is ideal for online learning environments, driver monitoring, or productivity tracking.

🚀 Features

• 👁️ Real-time eye tracking to detect prolonged eye closure

• 😮 Yawning detection using facial landmarks

• ⏰ Alert system that triggers an alarm when inattention exceeds a threshold

• 📊 Lightweight and efficient — runs on standard webcams

🛠️ Technologies Used

• Python

• OpenCV

• Dlib

• NumPy

• Real-time Image Processing

• Alert System

📷 How It Works

1. Captures video from webcam in real time.

2. Detects facial landmarks using Dlib’s pre-trained models.

3. Calculates Eye Aspect Ratio (EAR) and mouth openness to detect drowsiness or yawning.

4. Triggers an audible alert if the user is inattentive for a defined duration.