Inspiration
We are currently living global pandemic with a virus that is rapidly spreading. We looked towards preventing spread in one of the most congregated places in the community—the marketplace. Self-checkout stations are getting more use due to the lack of social interaction needed to checkout. However, in turn, they become hotspots for microdroplets that carry viruses. This is where our problem lies.
What it does
Instead of using the traditional touchscreen, we implement a machine learning model that uses gestures to navigate the UI of the self-checkout machine.
How I built it
We Implemented python and Yolo V5 for backend. For front end, we used JavaScript and HTML for our website.
Challenges I ran into
We originally had many troubles with integrating TensorFlow into a mobile app, but after talks with our mentors, we decided to use a different model instead.
What I learned
Prototyping with Figma is one of our biggest takeaways this hackathon.
What's next for MoPay
Improving the detection of gestures as well as widening the variety of usable gestures to navigate the UI.
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