SustainableSavour

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  Home Page

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  Generated Recipe

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  Firestore Database

Inspiration

We have noticed that people tend to go to grocery stores to buy food since they think they need extra food items or they don’t keep track of what items they have. Most of these items go to waste as they expire or go bad. Statistic here. As a solution, our innovation app allows users to use ingredients readily available to the store to eliminate the necessity of making unnecessary trips to the grocery store. In fact, food produces 8 tons of emissions per household! Additionally, we acknowledge the environmental impact associated with importing food items from other countries, which contributes to a substantial carbon footprint. In order to combat this issue and promote local sustainability, our web app provides a platform for local farms to showcase their produce. By offering recommendations based on the user's existing ingredients, we encourage them to explore recipes that require a couple supplementary items if necessary, thereby promoting local purchasing. This approach not only aids the environment but also supports the local economy. By emphasizing sustainability, we aim to alleviate concerns surrounding the availability of nutritious meals while reducing overall carbon footprint caused by food items.

What It Does

Introducing SustainableSavour, the innovative web app that revolutionizes the way you discover, enjoy, and contribute to a sustainable food ecosystem. With SustainableSavour, simply upload images of the ingredients you have, and our smart recommendation system will instantly generate delicious recipe ideas tailored to your available items. But that's not all! Our platform also connects you directly with local farmers, who can showcase their fresh produce and food items. By using SustainableSavour, you not only reduce food waste but also contribute to local agriculture by making sustainable food options more accessible to everyone. Join the movement today and savour a sustainable future with SustainableSavour!

How we built it

The planning and ideation stage entailed prototyping using Figma. We used Python to create the backend aspect of this web app which takes the YoloV5 and predicts the food items, based on an image uploaded. Thanks to this (https://recipes.eerieemu.com/api/recipe/) api, we used it to find a recipe with all the ingredients that were identified by the YoloV5 model. Using Flask, this was seamlessly integrated and a recipe was recommended to the user based on the food items they have. Using Tailwind CSS and Next.js, the web app was made and the backend of python was integrated. Next, we decided to work on creating a database so farmers can sign up and login, using Auth0. Farmers can upload their products and it would save with the help of Firebase.

Challenges we ran into

Time was a heavy concern as this is a hackathon as there were a myriad of features that we wanted to implement. To combat this concern, we focused on creating a minimum viable product with all the core features.

Another issue that we faced was integrating backend and frontend. CORS errors were preventing seamless integration between the frontend and the backend of the code, and finding a fix for the error was really mentally-taxing. At points, we felt like we wanted to give up.

Accomplishments that we're proud of

We are proud of completing a minimum viable product. We are proud of the website being able to read in an image and output a recipe. We are also proud of adding a feature where farmers can add products and have their

What we learned

Thanosan: During this project, I learned about how to integrate Firebase with Next.js, and how Firebase can be used for data storage. Through this project, I gained insight on how to store, retrieve and manipulate data. I also learned how to ensure effective database management.

Thuvaragan: I learned how to work with Flask for the ML model and how to integrate that with React, a framework I’ve never worked with before.

Ishnu: I learned UI/UX design with Figma.

What's next for SustainableSavour

To expand upon the technical demo and fully implement the Figma design onto the web app, so users can make use of all the features. Furthermore, instead of using the general YoloV5 model, we will train our own model in order to improve the accuracy of ingredient detection.

Built With

• auth0
• firebase
• flask
• react