VegLife

Landing Page
Login
Sign Up
Thank You!
Info Page About Your Journey
Choose Your Diet Journey
Main Dashboard
Shop
Upload Receipt to Earn Points Based On the Number of Vegan/Vegetarian Items You Get
Coupons to Help the User Buy More Vegan Groceries
All Of The Cryptocurrency That The User has Earned Is Stored Here
Offers For Today
Order Placed
Map of Nearby Companions That Have a Similar Diet Goal As The User
Example of a User With Similar Diet Goals
Leaderboard To Engage in Friendly Competition Against Other Companions To See Who Can Get The Most Cryptocurrency

Inspiration

Our inspiration for VegLife came from vegan and vegetarians' experiences when trying to purchase/consume food related to their diet. Furthermore, we wanted to give them a more motivational experience so we put a companion option to help them find others who are on a similar diet plan as they are.

veglife_info

What it does

VegLife is a mobile application that can help you on your journey to becoming a vegan, vegetarian or pescatarian with a growing community of people to help motivate you, rewards to encourage you and more. Using in-app cryptocurrency, users can buy vegan/vegetarian groceries with gift cards that are otherwise rather expensive. This way, people would stay motivated to following their diet goals. Next, there is also a AI built in the app which lets users scan the food and determine whether it is vegan, vegetarian or pescatarian. Last but not least, with the implementation of local companions to help them along their journey, people are bound to make a healthy difference on the health of the earth and themselves.

How we built it

We used Flutter, Dart, React-native, JavaScript for the front end. Tensorflow for the Machine Learning. MongoDB for the database and the UI/UX, is designed in Adobe XD. We used Express Server for the backend to handle routing and JSON web tokens for restricted routing. For passwords hashing, we used, bcryptjs.

Challenges we ran into

When we were trying to train the machine learning it crashed at certain times.

Accomplishments that we're proud of

We are proud that we learned about machine learning and we were able to make the app classify the different food diet categories.

What we learned

We learned how to make a TensorFlow machine learning model that has the ability to recognize images and a Flutter camera API.

What's next for VegLife

Our future plans for VegLife is that we would like to improve the app as much as we possibly can and then launch it into app stores worldwide to help everyone start and maintain their eco-friendly lifestyle.

Domain Name

dontbeahaterbeacreator.tech

Built With

Submitted to

BackyardHacks
- Winner Best Domain Name from Domain.com

Created by

I worked on machine learning model for live food scanning with flutter and tensorflow lite. Worked on flutter frontend and google map with google cloud API.

Andrew Yang
hmm, idk
I worked on the flutter front end and designed and implemented the user interface and user experience.

Sohil Athare
Sir John A. Macdonald Secondary School
I created the backend using MongoDB and express server. Then I created the react-native application and connected the backend with the app, and finally I edited the demo video

Saffat Aziz
Computer Engineer graduate from the University of Ottawa. Currently working fulltime as a Fullstack Software Engineer
Private user