/thetafoodcheck

"Helping You Make Healthier Food Choices with Personalized Insights"

Primary LanguageCSSMIT LicenseMIT

FoodCheck AI

FoodCheck AI is an innovative web application designed to help users make healthier and more informed food choices. By leveraging AI and blockchain technologies, FoodCheck AI analyzes food ingredients and provides personalized health insights based on the user's unique health profile.

Inspiration

Have you ever found yourself staring at a food label, unsure if it's good for you? We created FoodCheck AI to simplify this process. Inspired by the everyday struggle of making informed food choices, our app provides personalized advice, warnings, and recommendations to help users make the best decisions for their health.

What It Does

FoodCheck AI allows users to take a picture of food product ingredients and receive immediate feedback on whether the content is suitable for them based on their health data. The app provides personalized warnings, advice, recommendations, and interesting food facts to guide users in their food choices.

How We Built It

We built FoodCheck AI using a combination of powerful technologies:

  • Frontend: Next.js, Tailwind CSS, React Toastify
  • Backend: Next.js API Routes, Google Cloud Vision AI, OpenAI API, NextAuth.js
  • Database: MongoDB
  • Blockchain: Ethers.js, wagmi, RainbowKit
  • Cloud Services: ThetaEdgeCloud (Jupyter Notebooks)
  • Hosting: (e.g., Vercel, AWS)

Main Features

  • Personalized Insights: Get tailored advice based on your unique health profile.
  • Real-time Analysis: Snap a picture and get instant feedback on food products.
  • Health Warnings: Receive alerts for ingredients that may be harmful to you.
  • Educational Content: Learn about the ingredients in your food and their impact on your health.

Challenges We Ran Into

  • Issues with programmatic API access for creating deployments on ThetaEdgeCloud.
  • Time constraints limiting our development and testing phases.
  • Slow ThetaToken network performance impacting overall system responsiveness.

Accomplishments That We're Proud Of

  • Implementing secure authentication to protect user data.
  • Achieving a clear separation between frontend and backend, improving maintainability and scalability.
  • Developing an efficient API that meets the application's needs.
  • Creating a highly responsive and intuitive user interface.
  • Integrating access to ThetaEdgeCloud Jupyter notebooks for detailed health data analysis.
  • Developing custom algorithms for health data analysis based on standard benchmarks.
  • Introducing flexible pricing models, including subscription and pay-per-use options.

What We Learned

  • The importance of user data control and secure authentication in health-related applications.
  • A deeper understanding of AI-driven analysis for personalized health guidance.
  • The value of a well-structured architecture with clear frontend-backend separation.
  • Insights into the capabilities of ThetaEdgeCloud for advanced data analysis.
  • Challenges and opportunities within the ThetaToken network ecosystem.
  • The significance of flexible pricing models for user adoption and project sustainability.

What's Next for FoodCheck AI

  • Further optimization of ThetaEdgeCloud integration for more efficient health data analysis.
  • Enhancement of custom health data analysis algorithms for better accuracy and personalization.
  • Exploration of ways to improve ThetaToken network performance for better system responsiveness.
  • Expansion of Jupyter notebook integration for more comprehensive health insights.
  • Refinement of pricing models based on user feedback and usage patterns.
  • Investigation of solutions for more efficient API access to ThetaEdgeCloud deployments.
  • Continuous evolution of the platform to provide even more personalized health guidance.
  • Exploration of partnerships with health organizations to enhance the platform's knowledge base and credibility.
  • Implementation of user feedback mechanisms to continuously improve the UI and overall user experience.

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

  • Node.js
  • npm
  • MongoDB

Installation

  1. Clone the repo 
    git clone https://github.com/Bayurzx/thetafoodcheck.git
  2. Install NPM packages 
    npm install
  3. Set up your environment variables by creating a .env.local file and adding your configuration.
  4. Start the development server 
    npm run dev

Usage

  1. Sign up or log in to your account.
  2. Upload an image of a food product's ingredients.
  3. Get instant feedback and personalized insights.

Contributing

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Your Name - @your_twitter - email@example.com

Project Link: https://github.com/Bayurzx/thetafoodcheck.git

Acknowledgements

  • Google Cloud Vision AI
  • OpenAI API
  • Tailwind CSS
  • NextAuth.js
  • Ethers.js
  • wagmi
  • RainbowKit
  • Framer Motion
  • React Markdown
  • React Toastify
  • ThetaEdgeCloud
  • Jupyter Notebooks
  • Theta Token (TFUEL)

Check it out: https://thetafoodcheck.vercel.app/