“We see our customers as invited guests to a party, and we are the hosts. It’s our job every day to make every important aspect of the customer experience a little bit better.” - Jeff Bezos

Our inspiration for this project was to do just that; help customers shop as effectively as possible as well as help employees retrieve information about products as quickly as possible.

What Does It Do Exactly?

QRTailor is a B2B (Business to Business) company that sells customizable clothing tags with QR Codes that connect to a database with information about products. Companies who decide to use the QRTailor technology will allow their employees to have access to the app that can simply scan the QR Code on the label and retrieve information on the product, such as:

  • A Picture
  • Name & Description
  • Size
  • Colour & Available Colours
  • Quantity (Current Stock in the Particular Store)
  • Customer Review Ratings
  • Status (Availability Online or In-Store)

Employees can now have an in-depth perspective on all of the products, so when a customer asks a question such as, “Do you have this in red?” or “How many of these are left?”, all the employees need to do is scan the QR Code in order to properly respond to the customer’s concerns.

How we built it

The application uses OCR technologies provided by Google’s ML Kit to detect, read, and decode QR codes correctly. Furthermore, we used Android Studio to set up the application that the user will interact with. We also used Flask and Python, along with resource methods such as HTTP GET and POST to read from a minimal and decentralized database. We then set up the connection between the Android App and database by manually parsing incoming JSON files containing appropriately nested objects and attributes.

Challenges We ran into

Our lack of development skills was a big factor. Despite our back-end heavy hack, our development team had nearly zero back-end experience. Thus, we had trouble learning and using database technologies such as Firebase and Flask in a short amount of time. Furthermore, we dealt with Android Studio and it’s rapid updates. Most of the code examples were outdated and thus unhelpful. We also had to change our target-market half-way into the hack, as the app was originally meant for consumers to use until we realized it would make more sense for the employees. We lost a bit of time due to this and we missed out on some ideas that could have been implemented since the start, (such as an employee login screen).

Accomplishments that We're proud of

Despite the lack of developers in the team initially, through supporting each other and everyone learning very fast and effectively, we managed to implement an Android App using ML in time. We also added some bonus features to the App (for example, colour code the text) to improve user experience, which is very impressive. Lastly, we worked as a team very collaboratively and we encountered a lot of difficulties together, which really give us a sense of achievement when we reached our goal. Overall, it is a very meaningful hackathon for us!

What we learned

On technical aspects, we learned resource methods such as HTTP GET and POST. As we started to progress throughout the hackathon, we also started to experiment with many new techniques and tools such as Firebase, ML Kit, and design tools such as Figma. On the other side, through teamwork, we improved collaboration and communication skills. Furthermore, we learned that we should share responsibility and support each other as a way to increase team performance.

What's next for QRTailor

  • A more user-friendly GUI (graphic user interface)
  • Integrated chat interface between employees to share more information about products
  • Implementing a built-in interface to enter item entries for ease of use
  • Employee login page for individual access to view and/or manipulate store data
  • We have also used Figma to design a possible future prototype with a different interface that showcases a more optimal way our product can be designed. Figma Prototype Link
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