Inspiration
We look at statistics of infants that died in their sleep and we decided to make a difference.
What it does
It uses live object recognition to tell if the baby is in a dangerous sleeping position.
How I built it
We used OpenCV for image recognition with the camera of a raspberry-pi and a trained ML model running in the Jetson nano
Challenges I ran into
Setting up the database and cosntruscting the ML model
Accomplishments that I'm proud of
Constructing the ML model and learning a lot about computer vision in such little time.
What I learned
Terminal, openCV, Firebase management.
What's next for ModernBabyMonitor
Taking the temperature with the use of a thermal sensing camera and Google Home support.
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