!Drown

Inspiration:

Drowning is amongst leading death causes in the world. Lifeguards can help you, but he can't watch you 100% of the time.

What it does:

We have a Machine Learning and Computer Vision model to detect human and see if they are drowning or not. Then we will send it back to the server for assistance.

How I built it:

For the backend, we mainly used Python, TensorFlow, OpenCV, and other ML libraries. Whereas for the frontend, we put together a demonstration website by using HTML and CSS.

Challenges I ran into:

We only have 24 hours to come up with a cool idea and implement it. This year AuburnHacks doesn't have any specific topic, so our main restriction is our creativity.

Accomplishments that I'm proud of:

Effective teamwork

What I learned:

We learned more about complex ML models and their implementation as well as implementing new hardware we did not use before.

What's next for !Drown:

!DROWN does not end today. We would love to exhibit our product globally to save more lives.

Built With

• anaconda
• css
• html/
• machine-learning
• python