Inspiration
We wanted to create accurate diet plans, based on blood test results. Also, we wanted to scan a barcode and find the nutritional values of the product using this.
What it does
It scans blood test results and extracts the information, using Google Vision (text-recognition). Based on this, the app suggests diet plans to the user and checks whether products are suitable to eat (using the barcode to identify the product and its nutritional values)
How we built it
Divided the group on front-end and back-end development. Front-end team made use of the Ionic2 framework, Angular2 and Typescript in order to create a GUI and deliver data (text-recognition) to processing. The back-end team integrated various APIs together in order to deliver accurate diet recipes and decide whether a product is suitable for the user, based on his blood tests.
Challenges we ran into
Reading the 13 digit EAN of the barcode. Finding a recipe database. Synchronizing text recognition.
Accomplishments that we're proud of
Managed to develop the full application. Managed to use Google Vision (text-recognition) API.
What we learned
Advanced skills in Node.js Integrating multiple APIs together
What's next for MediDiet
Become a part of the NHS Five Year Forward View. #MakeADifference #MakeItBetter
Built With
- angular.js
- edamam-nutrition
- google-vision
- ionic
- node.js
- text-recognition
- typescript
Log in or sign up for Devpost to join the conversation.