FloodSafe

Inspiration

We're both from Georgia, where heavy rainfall and hurricanes have caused flooding increasingly often. In emergency situations, it can be hard to decide when it's time to go and where to go. We wanted to create a site that displays flood risk on a clear-cut numerical scale from and helps its users find optimal evacuation routes. The goal is to simplify the process to safety as much as possible, so there is one less thing to worry about when there are lots of hard decisions to be made.

What it does

FloodSafe takes a user's location and pulls geographical and weather data from Open Elevation, US Geological Survey, and National Weather Service. Using a built-in formula that currently considers elevation, predicted rainfall for the next 24 hours, and proximity to large bodies of water, the website calculates a RiskScore from 1-100 and then categorizes the location as low, medium, high, or very high risk. If the location is determined to be at high or very high risk, the program automatically begins to look for nearby cities that have low or medium risk and will output a suggestion to evacuate to. From there, the user has the option to be redirected to Google Maps, where the optimal route will be shown based on the data they entered into FloodSafe.

How we built it

In order to realize our vision, so we utilized the AI-powered code editor Cursor. We found APIs that we felt would best serve our purpose—OpenStreetMap, Open Elevation, National Weather Service, and US Geological Survey—and then asked Cursor to help us build a functional website with all the features we wanted. After verifying that the location lookup and subsequent data reports were accurate, we went back and manually created the RiskScore calculation method and cleaned up the user interface to be clean, intuitive, and informative.

Challenges we ran into

We are both aerospace engineering majors with minimal coding experience. We came into this hackathon with one MATLAB class, a couple Python projects, and a "hello world!" HTML file under our belts. When Alex came up with the idea to help people by integrating elevation, rainfall, and traffic data together, we both knew it was a project that could really make an impact, but we didn't know where to start. The first few hours were spent trying to find any platform to work on. We spent some time in VSCode and Vercel, but eventually ended up on Cursor. The AI-powered code editor helped us believe in the feasibility of our idea again, and we worked with the editor until we were at a point where we could go in manually and edit what we needed to.

Accomplishments that we're proud of

We are proud to have a working product that is able to integrate data from so many sources. We feel that a resource like this one could really help people simplify the evacuation process and get to safety when there is threat of flooding.

What we learned

Starting from almost rock bottom, we learned so much from this hackathon experience. We both tried to learn some code before the event, so we are walking away with more Python, JavaScript, and HTML/CSS knowledge than we started with. We learned what APIs are and how to use them. We learned how to use GitHub (kind of). We're so grateful for this experience and excited to learn more in the future.

Built With

• css
• cursor
• html
• javascript
• leaflet.js
• noaa
• nws
• openelevation
• openstreetmap
• usgs