Car Crash Detection App

It’s been almost one and a half year since I finished my thesis. I still remember those days -before even embarking on this new challenge- when I was really sceptical about which topic I should chose to work on. The truth is that none of the suggested areas appealed to my interests and that was making me really nervous.

It was that day that I read an article about a man who fell from his bicycle at a remote place and lost consciousness. His injury was severe and if it wasn’t for this little smart watch on his wrist, the whole situation could turn out to be a real tragedy! Fortunately the Apple Watch notified the biker’s family about a suspicious situation which moved them to action and finally saved their beloved father!

I was so intrigued about this Apple Watch spec that I immediately started searching about the technology behind. In a nutshell, Apple developed an algorithm which collects measurements from different watch sensors, analyses them and finally “understands” if something wrong is happening.

It was at this moment that I knew…what my thesis was going to be about. Next morning, I am crossing one of my favourite professors’ door and I immediately start talking about my idea. “I want to create an application for iPhone and Apple Watch devices which will save lives by detecting car crashes!” He was in! Simple as that… 6 months later, after studying Apple Technologies and doing plenty of research in terms of road accidents my demo version was ready!

Little did I now back then, that less than two years later I would see the exact same idea become an official Apple service! It makes me really happy to see that such an application finally exists out there and to such an extent that many lives are going to be saved from now on!

And…for those who are curious about how is this even possible… The key concept is that smart devices include numerous sensors such us gyroscope, accelerometer, microphone, gps and more. By continuously processing those data in real time, our phone or watch is able to know when something unusual and probably dangerous is happening.

Interested in learning more?

Link to my thesis

Link to the video demo I sent to my professor (in Greek)

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