The Intelligent Driving System (IDS) is an advanced driver assistance and data analysis platform designed to enhance vehicle safety and provide valuable insights into driving behavior. This project integrates computer vision, machine learning, and mobile technology to monitor driver actions, analyze data, and present insights through a mobile application.
- Real-time Driver Monitoring: Utilizes dlib and mediapipe libraries for facial landmark detection and gesture recognition.
- Data Analysis: Comprehensive analysis of driving data, including speed, location, and driver behavior trends.
- Mobile Application Integration: Provides users with insights into their driving habits and real-time location tracking using an A9G module.
- Raspberry Pi Integration: Optimized for embedded systems to enable seamless deployment in vehicles.
IDS/
├── src/
│ ├── dlib_model/
│ │ └── dlib_code.py
│ ├── mediapipe_model/
│ │ └── mediapipe_code.py
│ ├── data_analysis/
│ │ └── analysis_code.py
│ ├── mobile_app/
│ │ ├── coming sooooon
├── docs/
│ ├── IDS_Book.pdf
│ ├── IDS_Presentation.pdf
│ └── README.md
├── requirements.txt
└── LICENSE
- Running the Main Model
- Navigate to the source directory:
cd src/mediapipe_model
- Run the model:
python mediapipe_code.py
- Navigate to the data analysis directory:
cd src/data_analysis
- Run the analysis code:
python analysis_code.py
- Special thanks to El Shrouk Academy for the material and moral support they gave us.
- Special thanks to the creators of dlib and mediapipe for their powerful libraries.
- Gratitude to the open-source community for continuous support and contributions.
We'd like to acknowledge the following individuals who have contributed to this project:
Thank you for your valuable contributions!