What it does

Our app allows users to search for a product, and returns nearby stores that have them with their listed prices. It also lists individual sellers for the product nearby using database from sites such as Craigslist. Essentially, the app allows you to buy products one would purchase online and have a waiting period for in real time by showing stores and sellers nearby that sell the same product.

How I built it

We used Android Studio to create our app, using Java to design the back end and XML to design the front end. We used the Facebook API for the login credentials, google maps and google places to pinpoint stores and sellers nearby and Parse to import the sellers database from.

Challenges I ran into

  • While constructing the Facebook login, the API had issues generating the hash key for server recognition. We had to reconstruct the whole class and generate a new Facebook ID to sync our app with the Facebook servers.
  • Setting up the google maps was a hard task, especially getting the user's current location. Certain permissions had to be granted by the phone's location services for this feature to work properly.

Accomplishments that I'm proud of

  • Constructing the back end to manipulate databases and provide user with the seller's and it's product's details.
  • Designing an intuitive and easy to use UI for new users to easily adapt to the app.
  • Implementing the Facebook API so the user's details are automatically synced with the app.
  • Creating the app's logo with an elegant design, which focuses on the app's core idea.

What I learned

  • We learnt to use third party API's much better, essentially learning to use existing code to make tasks at hand easier.

- Setting up login security credentials with third party login providers such as Facebook was a new skill our team learnt.

What's next for ByBuy

We will develop algorithms that allow users to track a product over a period of time and allow them to purchase the product at the lowest price possible. Trends in discounts can be analyzed and the user will be notified as to when a purchase should be made for the best deal possible. These features allow the app to gain longevity and to sustain it's presence in the user's day to day and long term purchases.

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