Inspiration
We saw all of the raw data from the DC website and wanted to do something interesting with that. And after looking through the Capital One API, we knew we wanted to make people using banking services safer through data.
How it works
You type a DC address into the address bar and we find up to 10 closest and safest Capital One ATM locations. We have a ranking system (A, B, C, D) to show how relatively safe the ATM is in terms of recent crimes.
Challenges I ran into
The DC data hack website's data was in x and y coordinates, so we needed to tweak the data to be able to work with latitude and longitude. We also ran into a bit of a problem going through so much data and needing to optimize what exact data we wanted.
Accomplishments that I'm proud of
We had never worked with such so much data before, and we had never written GUIs or done so much design in a small amount of time. It was especially fun when we got the API calls working.
What I learned
We learned a lot about what it means to work with a lot of information and go through it efficiently. We also learned a bit of user experience.
What's next for ATM_Hack
The natural next step for ATM_Hack would be to make it a mobile app and using geolocation so that users don't need to input a location themselves.
Built With
- api
- awt
- big-data
- booz-allen
- capital-one
- dc-data-hack
- gui
- io
- java
- javax
- swing
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