foodbridge.ai

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Inspiration

Billions of tonnes of food go to waste every day, while millions of people struggle with hunger. FoodBridge AI was created to bridge this gap by making food donations more accessible and efficient. Additionally, many people are unaware of the nutritional value of their food, which can lead to unhealthy eating habits. The AI-powered nutrition scanner helps users make informed food choices.

What it does

• Facilitates food donations by connecting donors with those in need.
• Provides AI-powered nutrition analysis through a food scanner that helps users understand their meals' nutritional value.

How we built it

Next.js with Tailwind CSS for a modern, responsive UI. Gemini AI for analyzing food nutrition. Used styled UI components for a clean and interactive experience. Vercel for deploying the application

Challenges we ran into

• Integrating Gemini AI into the application was more complex than expected, requiring deep research and troubleshooting.
• Time Management: Balancing project development with school deadlines was tough.

Accomplishments that we're proud of

• Successfully integrating AI-powered food scanning.
• Building an intuitive and visually appealing UI.
• Completing the project within the deadline despite challenges.

What we learned

• How to integrate Gemini AI into a web application.
• Efficient use of styled UI components to improve user experience.

What's next for FoodBridge.AI

• Mobile App Version: Expanding to iOS and Android for wider accessibility.
• AI-Powered Recipe Suggestions: Users can get meal suggestions based on the food they have.
• Gamification & Incentives: Encourage food donations through a reward-based system.
• Community Partnerships: Collaborate with NGOs and food banks to increase impact.

Built With

• gemini
• html
• javascript
• nextjs
• react
• tailwind
• vercel