MealAid | Devpost

Inspiration

Nutrition is the foundation for good mental, physical and emotional health. What if we could intelligently leverage this fact to place individuals who have limited access to quality food sources in the best position to enable their success? Our team at MealAid was motivated by this idea and were led to develop a web app which allowed for users to

What it does

MealAid is a meal planning tool that leverages the power of machine learning and AI to not only predict global food inflation but, also create budget meals from its findings. The user is prompted to provide their country and a target date by which they want to calculate food inflation. From this input, our app uses machine learning algorithms and generative ai to create meals that consist of ingredients with the lowest inflation rates at the given target date. All in all, our tool is very scalable and has use cases for NGOs who are providing meal aid in developing countries or impoverished individuals. (UN sustainability and finance goals)

How we built it

We built this by leveraging many of the latest cutting edge technologies and platforms. We use Next14 as full-stack with Typescript and Tailwind and a Node.js backend. Our price predictions were made using a global food inflation dataset consisting of over 700,000 foods. To predict the changing food prices we implemented neural networks. From these prediction we used the OpenAI API to create sustainable meals from the ingredients we found earlier. MongoDB was used to store meals created by each user. To protect user data and provide exceptional personal user experience and authentication, we used Auth0.

Challenges we ran into

We ran into challenges posting transferring the data from our ML price predictor into our web-app.

Accomplishments that we're proud of

We're proud of the fact that we were able to produce a working project that addresses a real issue.

What we learned

We learned how to use Tensorflow library in JS.

What's next for MealAid

After this hackathon, the team plans on creating new iterations to our project to ensure that it functions as we envisioned, additionally we want to add more support and use cases with the data that the user provides.