DAASH

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DAASH (Disaster Assistance and Safety Helper)

Storms and floods and wild-fires, oh my! Need help with recovery solutions after a calamity? Need a plan before the event even happens? You're in the right place!

Inspiration:

The recent increase in natural disasters such as the fires in California and tropical storms around the world has caused damage that have cost a lot to many families; for some, even their lives. We created something that will help everyone plan for the next disaster and take precautions so that they are sooner able to return to their normal routines after these events occur..

What it does:

DAASH is a web app that provides useful disaster information in a user-friendly way. It pulls disaster data from FEMA and overlays it with news to give the user helpful insights into disasters happening around them. DAASH helps you find the current disasters occurring in different parts of the world and understand your home using reliable data.

How it was built:

We used Node.js for the backend, using APIs from FEMA, NewsAPI, and PredictHQ. We used a combination of JavaScript, HTML, and CSS to craft the frontend.

Challenges:

One of our main challenges was finding the best disaster dataset to use to populate our map. We also had to dynamically generate disaster markers from a dataset, which proved to be more challenging than we initially anticipated. Another issue we ran into was our accessing of past FEMA data. Since it was such a huge dataset we decided to create a database and store all disaster information in there.

What we learned along the way:

Ben - Learned more about interacting with Google APIs, also learned a lot from the interesting workshops & chats held during the time at PennApps.

Tanya - Learned where and how to find resources to achieve the goal and how to code on JavaScript.

Ronke - Learned about using different frond-end platforms and data manipulation with JavaScript.

Yuxi - Learned about utilizing services of Google APIs (especially Firebase that hosts our database).

Future:

Later on we plan on expanding the dataset and recreate it for many other neglected sections of the world and other different kinds of natural disasters. We also plan on making our map more specific, such as targeting U.S. counties for disaster frequency.

Built With

• css
• html
• javascript
• node.js