Inspiration
Protecting lives by detecting tired and distracted driving using cheap, effective tools.
What it does
EyeO tracks drivers' eyes to detect when they are falling asleep. If it detects a driver falling asleep, it sounds a buzzer and flashes a light to wake the driver. The device is small enough to hang from a car visor.
How we built it
EyeO was built by combining OpenCV, a computer vision library, with Dlib, a machine learning library. By taking video of a driver's face, we can determine the aspect ratio of open vs. closed eyes. If the driver's eyes are closed for too long, we sound an alarm.
EyeO runs on a raspberry pi and uses a web camera, so it would be cheap to manufacture and add to any car.
Challenges we ran into
Dependencies are hell. The raspberry pi has limited computational power. Lack of prior experience with C++.
Accomplishments that we're proud of
Jumping into a new, complicated technology stack and creating a working product in 36 hours.
What we learned
How to use OpenCV and Dlib. Patience.
What's next for EyeO
Recording drivers' overall wakefulness and uploading it to a web site so they can track their driving habits. Tracking driver wakefullness provides another metric for insurance companies that use driver behavior tracking devices.
Log in or sign up for Devpost to join the conversation.