Abstract
Driver Drowsiness Detection System is an open-source AI & Machine Learning project. Driver Drowsiness Detection System - Python-based Desktop application that uses computer vision and machine learning techniques to detect signs of drowsiness in drivers. Driver Drowsiness Detection System is a Python-based Desktop application that uses computer vision and machine learning techniques to detect signs of drowsiness in drivers. It is built using Jupyter Notebook, NumPy, Pandas, Python, scikit-learn. Key capabilities include: Real-time drowsiness detection; Three modes of detection (can be customized in settings):; Eye Aspect Ratio (EAR). The complete source code is publicly available on GitHub under the MIT License, making it a useful reference for students building an AI & Machine Learning mini project or final-year project.
1. Introduction
Driver Drowsiness Detection System is a Python-based Desktop application that uses computer vision and machine learning techniques to detect signs of drowsiness in drivers
2. Objective
Driver Drowsiness Detection System - Python-based Desktop application that uses computer vision and machine learning techniques to detect signs of drowsiness in drivers
This project demonstrates how Jupyter Notebook, NumPy, Pandas can be applied to a real-world AI & Machine Learning problem.
3. Key Features / Modules
- Real-time drowsiness detection
- Three modes of detection (can be customized in settings):
- Eye Aspect Ratio (EAR)
- Machine Learning based detection (using pre-trained models)
- Currently implemented model is trained on 42k images of drowsy and non-drowsy drivers.
- Trained with dataset contains 8 predictors.
- Fuzzy based detection (using fuzzy logic rules)
- Options to select various camera sources
- Mobile camera (via IP address)
- Car camera (if available)
4. Technology Stack
5. System Requirements
General requirements for this technology stack — check the README for exact versions.
- Python 3.8 or later with Jupyter Notebook / JupyterLab (or Google Colab)
- pip for dependencies
- Python 3.8 or later
- pip / virtualenv for dependencies
- VS Code, PyCharm or Jupyter Notebook
- Git (to clone the repository)
6. Installation & Setup
git clone https://github.com/surajgirioffl/Driver-Drowsiness-Detection-System.git
cd Driver-Drowsiness-Detection-SystemFull setup instructions are in the project README.
7. Future Enhancements
Suggested extensions you can add to make this your own project.
- Deploy the model as a web app with Streamlit, Flask or FastAPI
- Compare against an additional model and report the metric difference
- Add explainability (SHAP / Grad-CAM)
8. Viva / Review Questions
Common questions examiners ask for projects in this domain.
- What dataset does the project use and how was it pre-processed?
- Which algorithm / model architecture is used and why was it chosen over alternatives?
- How are training and testing data split, and how is overfitting avoided?
- Which evaluation metrics (accuracy, precision, recall, F1) are reported and what do they mean here?
- How would you deploy this model for real users?
9. Source Code & License
This project is developed by surajgirioffl and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.
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