Natural Disaster Tracker

An innovative project which addresses the problem that there's no representation of calamities, hence using Nasa's Earth Observatory Natural Event Tracker API, we created a webpage to do exactly that!

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Inspiration

Our inspiration of this project was how so much happens in terms of these catastrophes happening in the world and we barely get to know about it, let alone help. Therefore we thought to create a complete list accessible to anyone, so not only would they be able to track these calamities but try to help which is our biggest inspiration!

What it does

We created a webpage that has a complete list of these catastrophes, from there you can filter out events by the type of catastrophe, the coordinates, a radius around the coordinates as well as a time frame filter. All in all with this you can find a list of natural disasters that happened with a very specific criterion!

How I built it

We built it using Python and Flask for the API interactions and fetching the data and then represented the data using our HTML&CSS files. The API we used was NASA's EONET which is the Earth Observatory Natural Event Tracker.

Challenges I ran into

Challenges we ran into were sizeable as this is all of our first hackathon, from there the biggest problem was us trying to formulate our ideas and create an actionable plan. Once we circumvented that we took to many difficulties trying to create some aspects such as piecing together the API, then running all these other filters to finally get the final information.

Accomplishments that I'm proud of

We're really proud of what we learned, we're all very much in the beginnings of our computer science career and coming this far is just incredible. The feeling of pride in the final moments when it started working is unparalleled and something that was an amazing accomplishment.

What I learned

We learnt how to use so many different aspects of technology in harmony with each other, we initially were puzzled with all these different aspects such as HTML for the front end, API getting results, Python formulating those results but all in all that learning curve was amazing. Another thing was getting unstuck, this was a lot easier said than done but learning how to get unstuck took a while.

What's next for Natural Disaster Tracker

We want to build a graphical representation using a few more API's, therefore people can have a visual representation rather than a list, which would be a better representation.

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