RevRewards

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  Registration Page

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  Login Page

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  Small Business Map - used google maps api to mark small businesses on custom map, popup with business name shows when marker is clicked

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  Receipt Recognition Software - used duplicate rejection and text parsing with Tesseract OCR

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  Aggie Merch Incentive Shop - Use TamuTokens gained from shopping at small businesses to purchase A&M merch; progress bar implemented

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  Purchase Confirmation Page - collected email and address to ship merch; deducted tokens from current balance

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  Small Business Spotlight - Used ChakraUI grid to showcase small businesses, click takes customer to each respective business's site

Inspiration

In general, small businesses have a hard time gaining recognition. While we have been doing a better job promoting and supporting them in the past few years, there is still more work to be done, as they are just as valuable as our larger franchises. This inspired our team to create a project that helps these businesses thrive and rewards customers for shopping at said businesses. We are proud to introduce Reveille Rewards!

What it does

Reveille Rewards is a platform that encourages users to shop at local small businesses by offering a rewards system. Users can discover nearby stores, browse their products, and earn points by uploading a receipt of their purchase. These points can be redeemed for discounts at Texas A&M stores.

How we built it

Reveille Rewards was built using a modern tech stack. The front end utilizes React.js, Chakra UI, and the back end was developed with Django. Tesseract.js AP, a machine learning library for performing optical character recognition (OCR), was used to extract information from images of receipts. Work was divided evenly among the group to ensure successful completion of each project component.

Challenges we ran into

One of our most notable challenges was linking the Tesseract OCR system to the front end. Our original plan was to have the user upload an image of a receipt to a Django (backend-powered) form, have the receipt be processed in the back end, and then have it be sent to the front end. We found this workflow to be cumbersome to set up, so we instead opted to use a form in the frontend and just send the parsed data to the backend for processing.

Accomplishments that we're proud of

We are proud of successfully completing the project despite the numerous bugs and challenges we faced. Connecting an OCR system to a full-stack application was more challenging than we initially expected, so it was rewarding to see it work.

What we learned

We learned how to budget time effectively and coordinate well. Through holding regular meetings and checkups, we learned the importance of planning ahead.

We also gained experience working with machine learning/AI libraries like Tesseract, front-end technologies like React, and backend libraries like Django.

What's next for RevRewards

We hope to expand Reveille Rewards to encompass other satellite campuses besides College Station. We are also considering launching Reveille Rewards as a real product with added features and cross-platform support.

Built With

• axios
• chakraui
• django
• google-maps
• html/css
• postgresql
• python
• react
• tesseract
• vite