I am driving alone on a highway/interstate and all of a sudden met with any emergency, which might be a crash or any health issue. The chances of getting noticed by someone or someone calling EMS for me are higher when compared to the same incident that happened in a route without frequent traffic, which will usually happen when we take routes without tolls. So, the chances of getting rescued are very minimal in such scenarios.
What it does
Using Deep learning and facial recognition technology the user's (driver) face is continuously monitored. If there is any unusual activity captured, the application will beep an alarm in the driver's phone for a specific amount of time... if the unusual activity continues even after the alarm, the app will send a voice mail to EMS and the registered emergency contact number.
How I built it
The development is carried using python and for face recognition, we used Deep learning algorithms by Configuring OpenCV, DLib libraries.
Challenges I ran into
*There were several challenges while we were implementing the solution, there is no proper documentation available for configuring Dlib with OpenCV. *There are several verticals in this project, we faced issues with getting all these to a place to make boilerplate app with expected results.
Accomplishments that I'm proud of
*we were able to figure out different issues with OpenCV. *The configuration of OpenCV with Dlib.
What I learned
*How to Use OpenCV, DLib and to Configure DLib with OpenCV. *Learned Facial recognition techniques.
What's next for RescueMe
Integrating with GPS(car/mobile), Vehicle accident detection sensors, Heart rate Sensors. Notify the EMS with the current health condition of the victim like Allergies, if undergoing any medication, etc... prior to starting the necessary treatment.