NutriPlate

Making healthy eating affordable, accessible, and informative

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Inspiration

Although eating healthy is a major goal for most people, it can be difficult to know how to build a balanced diet in a way that is informed, affordable, and accessible. NutriPlate was created to simplify nutrition by helping users understand healthy food choices, explore affordable options, and feel more confident in planning nutritious meals.

What it does

NutriPlate helps users build balanced diets using guidelines from Canada's Food Guide. The platform organizes foods into macronutrient categories such as proteins, carbohydrates, healthy fats, and fibre, making it easier for users to understand what a balanced plate looks like and plan their grocery shopping accordingly. Users can browse different food options while comparing prices across grocery stores to make choices that fit both their nutritional goals and budget. To make healthy eating more practical and accessible, NutriPlate also includes an AI-powered recipe generator that creates meal ideas based on ingredients added to a user’s virtual cart. This allows users to discover simple, nutritious, and affordable meals while reducing food waste and making use of ingredients they already plan to purchase.

How we built it

We used React as our frontend and Django as our backend. We connected both technologies using RestAPIs which are sent between them. We also have AI support which was provided by IBM Watson which creates recipes quickly.

Challenges we ran into

We faced challenges deciding which IBM technologies to use and determining how our solution would align with one of the 17 UN Sustainable Development Goals. During development, we also encountered difficulties creating, manipulating, and retrieving data from the database, handling duplicate items, transcribing and parsing HTML text, and integrating IBM WatsonAI into our feature implementation.

Another major challenge was transforming AI-generated responses into reliable, structured, and usable data that could be consistently displayed within the application.

Accomplishments that we're proud of

  • Using IBM watsonx to create usable and informative data for ingredients, nutrients, and recipes.
  • Parsing Json files for data retrieval.
  • CSV file creation.
  • Using REST APIs for connecting backend to the frontend.
  • Working as a team to envision a concept into a tangible, usable, and effective product.

What we learned

How to create environmental variables, virtual environments, IBM technologies, REST APIs, using AI API calls, learning how to eat healthier, and how to eat affordably without sacrificing nutrition.

What's next for NutriPlate

  • Geolocation for finding nearest grocery stores, filtering food by dietary restrictions, showing effective substitutes for ingredients due to dietary restrictions.
  • More informative AI responses, filtering recipes by type (dinner, lunch, breakfast).
  • Codebase touchup.
  • Creating a scrapper to find discount flyers and add it to the database.

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