One of our team members, Andy, ended up pushing back his flu shot as a result of the lengthy wait time and large patient count. Unsurprisingly, he later caught the flu and struggled with his health for just over a week. Although we joke about it now, the reality is many medical processes are still run off outdated technology and can easily be streamlined or made more efficient. This is what we aimed to do with our project.
What it does
Streamlines the process of filling out influenza vaccine forms for both medical staff, as well as patients. Makes the entire process more accessible for a plethora of demographics without sacrificing productivity.
How we built it
Challenges we ran into
Getting Azure's Vision API to get quality captures to be able to successfully pull the meaningful data we wanted. Front-End to Back-End communication with GCP NLP functions triggering events.
Accomplishments that we're proud of
Successfully implementing cloud technologies and tools we had little/no experience utilizing, coming into UofTHacks. The entire project overall.
What we learned
How to communicate image data via webcam and Microsoft Azure's Vision AP and analyze Optical Character Recognition results. Quite a bit about NLP tendencies and how to get the most accurate/intended results when utilizing it. Github Pages cannot deploy Flask servers LOL. How to deploy with Heroku (as a result of our failure with Github Pages).
What's next for noFluenza
Payment system for patients depending on insurance coverage Translation into different languages.