We felt the need for this product in long range driving as it is natural for a driver to feel sleepy during such times but is indeed fatal for him and others as well. Our inspiration stems from a desire to combat this problem at a feasible level.
Jhapki helps the driver stay safe by looking out for symptoms of drowsiness. It timely alerts them of this development so that immediate actions can be taken to remedy the situation on the road.
We used computer vision library (cv2) to detect a person's blink. The data about blinks is then used to conclude about the state of the driver. This sets off an alarm in the front end of the application and takes other helpful measures as well.
We are proud of the fact that this program can be deployed in real-time computation due to its low-overhead and high accuracy in detecting a person's blnk. Even one life saved is a matter of pride for us.
Helping Jhapki reach a mass audience is a dream for us as we can't help but stress the need for this product. Right now, only a handful of very high-end luxury cars like Tesla support this feature. Bringing it to an average driver on the highway would be a moment of pure elation for us.
- node.js
- python
- javascript
- express.js
- howler.js
- computer-vision
This Project was made collectively by Mansi Breja, Rahmeen Habib, Akshita Aggarwal and Sarthak Tandon as a part of Hack@BVP2.0, September 2018.