We were inspired to build Leonardo after we realized that businesses might not have the resources to research the purchasing habits of customers in their neighbourhoods. We wanted to create an application that allows businesses and other individuals to find out where, when and how people spend their money, which not only helps them make financial decisions, but also lets them monitor employee spending with company money.

What it does

Leonardo draws a heat map of where transactions are being made, and lets the user filter these transactions by a minimum amount. The user can also decide the time-periods of the transactions, and look at how spending data changes over time.

How we built it

We began by accessing TD-Davinci API, but soon realized a variety of limitations with the technology. We then decided to use local transaction data, and parse the information for key information. We generated JSON files of the transaction locations, amount, and merchants, and accessed this through Java in android studio. We incorporated the Google Maps + Heatmap APIs, and parsed the JSON data to plot it into a map. We then added sliders to allow users to manipulate the data they see.

Challenges we ran into

  • Limitations of the Davinci API
  • Using the heat map API
  • Parsing JSON data

Accomplishments that we're proud of

  • It works!

What we learned

We learned how to use a variety of new technologies, particularly TD's API, the heat map API, how to deal with complex JSON data, and advanced programming in node.js.

What's next for Leonardo

We hope that we can extend Leonardo to the whole set of TD data, as well as clean up the look of the app and provide secure, meaningful information that the user is looking for.

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