Hurricane SOS

Inspiration

(1) Hurricanes are the top 3 natural disasters that cause great damage to people's safety and wealth in south-east area, and Houston in specific. (2) In a time when media are more and more decentralized, posts on text-based social media featured by twitter can report real time news even faster than regular medias. We'd like to scrap these data and make them helpful in hurricane rescue.

What it does

Ideally: (1) Having a backend data scraping function that dynamically selects twitter post about real time damage report based on user's current address, and (2) Providing the closest shelters to the user's current location.

How we built it

html/css/js frontend, python backend, flask web-app

Challenges we ran into

There's something wrong with our frontend dependencies, so we didn't accomplish stitching it up together with the backend. We think the hardest part is that we spend our whole hackathon figuring out the request sending process through http.

Accomplishments that we're proud of

Figured the whole MVC routing with flask, would like to further implement on flask We also have great GUIs (ideally, we can display twitter posts as htmls embedded in our frontend through the twitter api)

What we learned

What's next for Hurricane SOS

(1) Fix connection between frontend and backend. (2) Apply Google Cloud NL AI on twitter data scraping so that it filters twitter smartly and returns the address indicated in the post together with post itself. (so that we can store them and update on our backend)

Special thanks to AJ Soud and Michael Bell who taught us so much about full-stack development using flask! We tried really hard;;

The Youtube video is unrelated, but all of us were in the dance so enjoy ;-)