Inspiration

The Hawaii incident with ballistic missile text a couple years showed there would be a need for better warning systems and the idea of better the information of first responders.

What it does

The device takes data from Raspberry pis then runs machine learning to determine how many people may need help given the population data, and weather data. This will help rescuers prioritized the area need the most help and allocate resources accordingly. In addition when bad weather occurs a notification will be sent out.

How I built it

We have a raspberry pi that has a bunch of sensors in the that pushes data to a virtual Linux Machine in gcp. The Linux machine than take the data and predict the amount of people that would need help in that area, and contacts people if the weather is bad. Then there is a front end that creates a way for people to sign up for the service.

Challenges I ran into

problems with Firebase, Domain registrar, and FTP library Using Machine learning for first time

Accomplishments that I'm proud of

We were able to write a program that can learn with data, figured out fire base, and the fact that we are a team of a with four different types of majors.

What I learned

We learned alot about the gcp, machine learning, and hardware we were using.

What's next for WIMS

We would take in more data to better our program. We could even turn this into a charity to help insure

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