💡Inspiration: After 2 other attempts at ideas that weren’t possible due to the lack of adequate materials, we decided on using computer vision to make a proactive solution in the way we approach road safety through self-assessment.
👀 What it does: Provide early detection of potentially dangerous driving in drivers (e.g., fatigue, impaired, etc.).
❓How we built it: Utilized computer vision and image manipulation to measure pupil dilation over time to measure reaction time and test impairment.
😰 Challenges we ran into: Detecting pupil from grey scale image.
💪 Accomplishments that we're proud of: Learbung and creating a computer vision software for our 1st hackathon to solve a real world problem.
📝 What we learned: Dlib, OpenCV, Figma, Git, GitHub.
🔮 What's next for SAS: SEE and STEER: Utilizing machine learning to provide more accurate results to users. Being able to detect a wider shade of eye colours. And work with taxis and businesses like Uber to commercialize the product and increase road safety.
Built With
- figma
- python
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