NutriMap

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  Map view showing nearby food markets for buying ingredients

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  User gives input of ingredients, cuisine, age, dietary restrictions etc.

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  Recommended recipe based on user's input

Problem Statement: Design a tool to suggest healthy meals and find fresh food nearby.

Inspiration

The inspiration behind NutriMap stemmed from the growing need for personalised nutrition solutions. With busy lifestyles and varying dietary needs, people often struggle to maintain healthy eating habits. We wanted to create a tool that not only simplifies meal planning but also ensures fresh, locally sourced ingredients are at the heart of every meal.

What it does

NutriMap is an AI-powered meal planning tool that combines personalized nutrition with real-time fresh food sourcing. It uses Google Gemini to generate age-specific recipes and offers six customization filters, including dietary preferences and ingredient constraints. Smart geolocation identifies nearby grocery stores, and generative AI suggests substitutions while adapting recipes based on life stage. It’s a closed-loop system that connects personalized meal ideas with fresh, local ingredients.

How we built it

We built NutriMap using a combination of cutting-edge technologies. Google Gemini powers the recipe generation, while Google Maps APIs enable smart geolocation for sourcing fresh ingredients. The AI-driven customization engine uses machine learning to adapt recipes and suggest substitutions. The front-end was designed for user-friendly navigation, and the back-end integrates seamlessly with third-party APIs for real-time data.

Challenges we ran into

Integrating multiple APIs and ensuring seamless communication between them was also complex. Additionally, fine-tuning the AI to generate recipes that are both personalized and practical required extensive testing and iteration.

Accomplishments that we're proud of

We’re proud to have created a tool that bridges the gap between personalized nutrition and fresh food sourcing. The integration of generative AI for recipe adaptation and substitution suggestions is a standout feature. We’ve also successfully built a closed-loop system that ensures users can easily access fresh ingredients for their customized meal plans.

What we learned

Throughout this project, we learned the importance of balancing user customization with practicality. We also gained valuable insights into integrating multiple APIs and leveraging AI to solve real-world problems. Collaboration and iterative testing were key to overcoming technical and design challenges.

What's next for NutriMap

Next, we plan to expand NutriMap’s capabilities by integrating with more grocery stores and farmers' markets, enhancing the AI’s ability to handle diverse dietary needs, and adding features like meal prep guides and nutritional tracking.

Built With

• python
• streamlit