Aloecate

A budgeting application that used to help users manage their money and plan a budget. Includes features such as a receipt scanner and a purchasing position cluster to better the user experience.

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Inspiration

We decided to make a application that would make our lives easier. Decided to add features we would like to see in a budgeting application. Made something that we would enjoy using.

What it does

Analyzes user data and translates it into a user interface that is easy to understand. Multiple forms of data collection: via user input, image recognition and google maps API position recognition. Applies searching and grouping algorithms to analyze data and create trends.

How we built it

Used the google API to map location and place markers for frequently shopped places. Used and trained Tesseract OCR, employed various scripts to optimize processes. Transfer data using CSV files. Front end made using Bracket.

Challenges we ran into

Increasing the accuracy of the OCR software. Connecting back end to front end.

Accomplishments that we're proud of

ML implementation and training and OCR API. Developing front end graphs and data and using them to present back end data from CSV and JSON files.

What we learned

Implementing various APIs and using ML to search through images and collect data from them.

What's next for Aloecate

Further improving accuracy and efficiency and managing using data using a server.

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