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Shantanu10z / repository
A real-time driver drowsiness detection system using Python, computer vision, and Arduino-based hardware alerts.
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A real-time drowsiness detection and alert system using computer vision and embedded hardware to prevent fatigue-related accidents.
pygameDrowsiness Alert System/
│
├── screenshots/ # 📸 Demo images & architecture diagrams
│ ├── circuit diagram.jpg # 🔌 Circuit schematic
│ ├── Picture1.png - Picture4.png # 🧑💻 Live detection snapshots
│ ├── Picture5.jpg - Picture6.jpg # 🛠️ Hardware setup
│ └── usecase.png # 📊 Use Case Diagram
│
├── sketch_apr9a/ # ⚙️ Arduino motor control code
│ └── sketch_apr9a.ino
│
├── venv/ # 🐍 Virtual environment (ignored)
├── yawn.py # 🧠 Main Python detection script
├── shape_predictor_68_face_landmarks.dat # 🎯 Dlib face landmark model
├── haarcascade_frontalface_default.xml # 👁️ Haar cascade for face detection
├── Alert.wav # 🔊 Audio alarm
├── arduino_code.txt # 🔁 Serial command protocol reference
├── requirements.txt # 📦 Python dependencies
├── PROJECT REPORT.pdf # 📘 Detailed report
├── LICENSE # ⚖️ License info
└── README.md # 📝 This file
Selected from shared topics, language and repository description—not editorial ratings.
Kesihambigai22 /
AI-powered Driver Monitoring and Vehicle Anomaly Detection System using ESP32, OpenCV, MediaPipe Face Landmarker, EAR-based drowsiness detection, and real-time RPM anomaly monitoring.
64/100 healthShivamMathtech /
This project is an advanced 5-axis AI-powered robotic arm system built using: ESP32 Arduino Mega PCA9685 Servo Driver Computer Vision AI Learning Models Real-Time Motion Planning
63/100 healthClone the repo:
git clone https://github.com/Shantanu10z/drowsiness-alert-system.git
cd drowsiness-alert-system
Create a virtual environment:
python -m venv venv
venv\Scripts\activate (on Windows)
Install dependencies:
pip install -r requirements.txt
🔄 Install dlib manually if needed:
pip install .\dlib-19.22.99-cp37-cp37m-win_amd64.whl
start signal to Arduinostop signal.| Detection Demo | Hardware Setup |
|---|---|
|  | |
This project is licensed under the MIT License. See the LICENSE file for details.
khaledmohamed574 /
Smart Driven is a real-time Driver Monitoring System that uses computer vision (EAR, PERCLOS, MAR, head pose) and Arduino sensor data (steering, speed, throttle) to detect driver fatigue. Built with Python, OpenCV, and dlib. Calculates a weighted fatigue score and triggers visual and audio alerts when drowsiness or yawning is detected.
59/100 healthAI-powered safety system using Computer Vision & Arduino to detect driver fatigue in real-time. Features automated facial analysis and an integrated braking mechanism for accident prevention. Demonstrates expertise in Embedded Systems, Python, and hardware-software integration
49/100 healthA real-time Computer Vision system built with Python, OpenCV, and dlib to detect driver drowsiness and fatigue. It monitors eye closures and head tilt via a webcam, triggering a dual-alert system: an audio warning on the computer and a physical buzzer activated via serial communication with an Arduino.
42/100 healthprafulgeorge /
A real-time driver drowsiness detection and alert system using OpenCV, Geopy, and Arduino. Detects prolonged eye closure, triggers alarms, and sends GPS-based emergency SMS alerts via Twilio. Showcases hands-on integration of Python, computer vision, and IoT for road safety applications.
49/100 health