storm repair analysis

Inspiration

In light of the recent storm events i wanted to create an a web app that analyses past data to predict areas that are at high risk of storm events. Using that data and the cost of repairs to create a tool where we simulate as a storm

What it does

Using that data and the cost of repairs to create a tool where we simulate as a storm as it passes through showing in real time average cost repairs. It also shows simulations of past events etc and their average cost of repairs. Be able to filter by storm risk (%), gust, temperaure etc. It is meant to be used as a tool for governements to assess high risk areas of storms and allocate the right amount of money to help with repairs. Could also be used for the general public to check areas of high storm frequency.

How we built it

uses fastapi backend with a react frontend and a machine learning models to simulate data. from the simulation of the data I presented it as a animation to show a preview of what it may look like.

Challenges we ran into

wifi, rate limiting of api calls couldnt load data fast enough.

Accomplishments that we're proud of

a working web app that simulates the average repair costs for certain areas

What we learned

if you live in the north, northern ireland, or west england you are most susceptible to storms.

What's next for storm forecast

Improved machine learning algorithm to have more historical data and more rich data to improve models authenticity. Add disruptions to transport and road blocks.

Built With

• fastapi
• machine-learning
• react