Co-Passenger
Stays up when you tend to fall asleep
Created on 17th February 2020
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Co-Passenger
Stays up when you tend to fall asleep
The problem Co-Passenger solves
We have seen a steep rise in road accidents in the last few decades. The lifestyle of today’s generation has made it obvious to commit a mistake while driving. While automated driving systems are being studied upon, human surveillance is yet very important. The biggest killer out of all the accident reasons is drowsiness while driving. Our purpose in this paper is to save people from such hazards. We are using nature’s gift, i.e. blinking pattern, to analyze and predict if a person is drowsy or tending to fall asleep. Once implemented, our system of vigilance and monitoring detects various patterns in the blink pattern of the person driving and gives him an alert at the earliest to avoid any mishappening.
Challenges we ran into
Our first and prime problem was to create a data set that would satisfy diverse types of eyes that we see in daily life. Also, the dataset needed to be formatted in such a way that it did the required work efficiently in less amount of time. Lastly, the challenge that we faced was to connect the python script with external hardware to make it work in a real-life situation.
Technologies used