Inspiration
Roughly one-third of the food produced that is intended for human consumption every year- around 1.3 billion tons and valued at USD$1 trillion- is wasted or lost. Food commonly gets thrown out because they've expired or turned rotten. With extra food being thrown out because they're not used, we're hoping our app will be able to identify recipes with actual ingredients found in a person's house. This way, they can be used rather than thrown out with the other garbage.
What it does
Our big goal is to eliminate food waste! Roughly one-third of the food produced that is intended for human consumption every year- around 1.3 billion tons and valued at USD$1 trillion- is wasted or lost. This is enough to feed 3 billion people. And, food waste ends up wasting a quarter of our water supply in the form of uneaten food. That’s equated to USD$172billion in wasted water. (Source: earth.org).
This is our big why. We know that people don’t intentionally waste food - we love eating! But, there is too much wastage, and this is something that we know we can change. We also wanted to bring more joy and happiness into it too! And that birthed our idea of Leftover Magic!
Leftover Magic allows you to be an innovative chef without buying elaborate ingredients and without expensive recipes - all the while ensuring that you're not throwing away your leftover ingredients! How does it work?
All you have to do is take a picture of your leftovers. Then let Leftover Magic do its magic! It will identify the ingredients in your picture, and come up with recipes from all over the world, ranked in an order that prioritizes meals that match your current suggested diet (through our connection with WeightWatchers and MyFitnessPal), fall into your favorite cuisines (chosen in your profile), and maximizes all your ingredients to make sure you don't waste anything and end up coming up with an innovative and fun meal instead!
How we built it
We first brainstormed a list of ideas for the different tracks before deciding on our food waste app. Then, we built it using Figma where we wireframed our design and created a mock-up of our app.
Challenges we ran into
This was our first time with the goal of building a seamless front-end prototype, and it was challenging! As we were brainstorming and developing our idea for Leftover Magic, we had so many ideas that we came up with and integrations that we wanted to include with other apps. The biggest challenge was implementing all our ideas. We were able to create our Google Cloud Vision API key, but there was so much to learn and explore there - that we didn't get a chance to connect it with a React Native app yet. Thus, we're hoping to transform this challenge into a future goal and work on making our app a full-stack finished product soon!
Accomplishments that we're proud of
This is both of our first times using Figma. All the tools and layout were new to us and we experimented a lot with designs and component interactions before we came to our final app mock-up. With our previous wireframes, we never used prototype interactions so that feature was something new to us that we managed to figure out.
What we learned
While going through the process of creating our Figma wireframe, we learned the importance of having a detailed mock-up. We learned how to make the different frames interact with each other which helped us narrow down the specifics of our app functions. In addition, we learned how to create a user-friendly design with clear labels and make the most important labels and content more centered and larger on the screen.
What's next for Leftover Magic
Now that we have our mock-up, we want to use React Native to create the front end of the app. Then we want our app to identify the foods in the photos by using the Google Cloud Vision API and use the categories that they identify in the MealDB API that can produce the recipes using those ingredients. Finally, we would like to add a favorites page to enhance user experience so users can store commonly used recipes in the app.
Built With
- ai
- figma
- google-cloud
- meal-db
- photo-recognition

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