Inspiration

According to the National Highways and Traffic Safety Administration, 3000+ people a year die from distracted/drowsy driving. Upon learning this, we wanted to implement a system to help mitigate this problem.

What it does

Our system provides safety features that can detect and alert a driver when they are distracted or sleepy, hence alerting them of their state and allowing them to re-focus.

How we built it

We created our system using the languages C++ and Monkey C for OpenCV and Garmin SDK respectively. From OpenCV we tracked our user’s eye and head movements and from Garmin SDK we tracked our user’s heart rate. If any of these tracked metrics fell above/below a certain threshold we would set off an alarm.

Challenges we ran into

As beginners to C++, we both learned both basic and advanced implementations of this language. Aside from the actual coding, we ran into a lot of issues compiling it to run programs at all.

Accomplishments that we're proud of

We are proud to create a reasonably accurate detection system that can gather real data from users, instead of drawing from generated data or theoreticals. This shows that our project could have real benefits if cleaned and implemented properly.

What we learned

We developed and sharpened skills in learning new languages with C++ and Monkey C to implement OpenCV and Garmin SDK. We also worked with quick processing of real-time data to ensure our alarm systems were robust enough to warn the users quickly.

What's next for Unsafe Driving Detection System

We hope to implement a more comprehensive analysis of the cognitive wellbeing of a driver. Some next steps that we would like to implement are an EEG sensor, Drunk Driving detection through infrared camera, or other sensors. Along with that we would like to integrate a more robust alarm system that could possibly signal to law enforcement or trigger a system in the car to make it safer for a driver under these conditions.

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