Storm Stoppers | Devpost

Inspiration

After seeing the devastation that occurred after Hurricane Ian, we were interested in seeing if there was a way that we could predict the amount of deaths and injuries prior to any storm hitting, so we can better prepare for the outcomes of the storm.

What it does

It allows us to see if there is a relationship between deaths and the event type, month, year, and state. We can further use this to predict the number of deaths so that we can better prepare for these storms in the future to minimize the number of deaths and injuries.

How we built it

We utilized python and R programming language to analyze the data. We first cleaned the data through python and pandas and then created our models on RStudio. We wanted to see if we could predict the number of deaths based on event type, month, year, and state.

Challenges we ran into

Challenges we ran into were slow IDEs, visualization and processing of big data, and language barriers between python and R.

Accomplishments that we're proud of

Taking on a larger data set, utilizing our knowledge to analyze a data set, discussing our desires and goals for our dataset and how we want to interpret it, and decision making.

What we learned

We learned how to manage bigger data sets utilizing RStudio and finding the best models based on the data that we were given.

What's next for Storm Stoppers

We can continue to work on the models and create more models to predict the number of deaths based on the event type, month, year, and state. We can utilize different types of regression and create more visualizations as well.