FoodScan is a Web3-powered food safety analysis platform that leverages AI models to analyze food ingredient lists, providing comprehensive safety assessments and recommendations. We are committed to making food safety information more transparent, trustworthy, and putting data ownership back in users' hands.
- AI Safety Analysis: Upload ingredient lists for instant safety analysis and scoring
- Risk Assessment: Identify excessive additives, potential allergens, and other safety concerns
- Improvement Suggestions: Receive professional food safety improvement recommendations
- Data Traceability: Blockchain-based ingredient information storage ensures data authenticity and traceability
- Community Building: Token incentive mechanism encourages user participation in data verification and algorithm optimization
- Decentralized Data Storage: Utilizing blockchain technology to ensure data authenticity and traceability
- User Incentive Mechanism:
- Token Rewards: Participate in data verification and error correction
- NFT Certification: Special privileges and certification for quality contributors
- Data Sovereignty: Users have complete control over their personal data, ensuring privacy and security
- Smart Contracts: Automated contribution rewards distribution and community governance
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Frontend:
- Next.js 13 - React Framework
- TypeScript - Type Safety
- Tailwind CSS - Responsive Design
- RainbowKit - Web3 Wallet Integration
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Blockchain:
- Thirdweb SDK - Web3 Functionality Integration
- Solidity - Smart Contract Development
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AI/Data:
- OpenAI API - Ingredient Analysis
- IPFS - Decentralized Storage
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Clone the repository:
git clone https://github.com/jiantao88/FootScan.git
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Install dependencies:
npm install
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Configure environment variables:
- Copy
.env.example
to.env
- Fill in required API keys:
- Thirdweb Client ID
- OpenAI API Key (if using)
- Copy
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Start the development server:
npm run dev
Create a .env
file and add the following:
NEXT_PUBLIC_THIRDWEB_CLIENT_ID=your_client_id_here
OPENAI_API_KEY=your_openai_api_key_here
MIT