https://github.com/ferasaljoudi/capstone

https://github.com/ferasaljoudi/capstone

Last synced: 7 days ago
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• Host: GitHub
• URL: https://github.com/ferasaljoudi/capstone
• Owner: ferasaljoudi
• License: mit
• Created: 2024-09-30T17:51:38.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-11-07T16:18:50.000Z (12 days ago)
• Last Synced: 2024-11-07T17:28:03.051Z (12 days ago)
• Size: 1.18 MB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md
  • Security: SECURITY.md

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README

        


    








    






- We are developing a driver detection system that alerts when it detects eye closure to prevent drowsiness-related accidents.

- The system uses a camera and a machine learning model running on a Raspberry Pi 5 to monitor the driver’s eye activity in real-time.

- The main goal behind our project is to enhance road safety by offering an affordable, offline solution that reduces accidents caused by drowsy driving.

- Unlike detection systems in expensive high-end cars, our solution is `affordable`, `standalone`, works `offline`, and can be installed in any vehicle, making it more accessible to a broader audience.






    






  Implementation Details

  


  Our solution involves using a camera with Raspberry Pi 5 to monitor the driver’s eyes in real-time. We will implement a machine learning model, likely a Convolutional Neural Network (CNN), for accurate eye closure detection, leveraging OpenCV for image processing. The system will sound a buzzer when drowsiness is detected.




  What Makes Our Solution Unique

  


  Unlike existing systems in luxury vehicles, our approach is affordable, works offline, and can be installed in any vehicle. This makes it more accessible to everyday drivers.




  Target Audience

  


  We aim to serve drivers looking for a cost-effective way to improve road safety without needing high-end features found in premium cars.






    






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