Inspiration
As college students, we often have many impulses to buy things, but we often don't have enough money or spend it too rashly. We hoped that we could create an easy way to keep track of our spendings and give ourselves an overview of how we actually spend our money.
What it does
Our app takes two kinds of inputs, photos of receipts or manually inputted data from the user. We then process this data to keep track of spendings for the user and analyze the user's spending habits.
How we built it
We used mainly used Android Studio to code everything. We implemented some open source APIs to get the photo of the receipt and other APIs to analyze/display the data collected. Also, we used Google's Firebase to store our data whilst using its built-in ML Kit to use image processing (text recognition) to scrape the data from the photos of the receipts.
Challenges we ran into
The main challenge we faced was combining and implementing multiple APIs so that everything ran smoothly.
Accomplishments that we're proud of
We feel that our main challenge is in fact our greatest accomplishment. Combining multiple codes is harder than writing your own code. To combine different codes, one must have a clear idea of everything in order to understand other people's code, and furthermore use them so that they all work as one. On a side note, we were super excited to be able to successfully scrape text from a photo.
What we learned
We learned the importance of version control and the significance of communication within the group. In the beginning, we were really "messy", with each individual working on their own ideas and no one having a clear idea on the final state of our project. To solve this, we decided to constantly hold short "power meetings" to update each other on our current progress and furthermore discuss potential issues. All this was of course accomplished through version control.
What's next for Captain Logger
There are actually many features we hope to work on but just didn't get to due to time constraints. Some include writing our own machine learning/data science algorithm to analyze spending habits (we have yet to discuss the specifics as this would require a lot of data), or even informing the user to cut down on spendings in a specific category based on the analyzed data.
The Fish Market
Captain Logger was mainly built towards the contest "The Fish Market". Needless to say, our project fits the contest goal completely as it acts as a handy financial aid.
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