AthleteIQ is a decentralized application designed to help athletes track their performance, manage training data, and receive AI-powered insights while ensuring data privacy through zero-knowledge proofs (ZKPs). The platform leverages blockchain technology for secure storage, smart contracts for reward distribution, and a tokenized incentive system to gamify training.
- code in
Backend/zkp_login/src/main.rs
- get JWT from OCID
- Decode JWT
- Get Salt POST /api/auth/salt [JWT]
- Blake twice using [aud, sub, salt, email] => 128 bytes
- Do Keccake256 => 64 bytes
- Derive ETH using Keccake256 seed
- POST /zkproof [aud, sub, salt, email, address]
- Get Decoded JWT
- Blake twice to get 128 bytes hash
- input [Blake, address] to Exapander circuit
- Do keccak256 inside circuit
- use hint to derieve ETH address from keccak256 seed inside circuit
- compare hint output with circuit expected output => (output == address)
- generate witness, compile proof
- return witness + proof
- sign message contains date+ proof + ETH address
- send to frontent
- Query Sepolia Smart contract with signed message + address
- decode message
- check is right signare?
- check date > now
- check (client address) == (proof address)
- True? allow signin
- live at sepolia.etherscan.io/address/0x00EA3c8270868B9cF9C24a5E78cACDa9DfE8B485
- code:
Contracts/packages/hardhat/contracts/YourContract.sol
- Decentralized athlete profiles.
- Stores personal details, performance metrics, and training history.
- Secure, keyless access using zkLogin.
- AI/ML-powered analysis of training data (e.g., running times, heart rate).
- Privacy-preserving analytics using zkML.
- Personalized training recommendations.
- Immutable recording of competition results on the blockchain.
- Efficient result verification via GKR compression.
- Automated reward distribution via smart contracts.
- Athletes earn Iten tokens for training and competition achievements.
- NFTs for milestones (e.g., completing a marathon).
- Gamified leaderboards and achievements.
- Controlled sharing of performance data with coaches, scouts, or sponsors.
- Zero-knowledge proofs (zkSNARKs/zkSTARKs) for privacy-preserving data sharing.
- Flask: Backend framework.
- MongoDB: NoSQL database for storing user data.
- IPFS: Decentralized storage for large data files.
- TensorFlow.js/Python: AI/ML for performance analysis.
- zkSNARKs/zkSTARKs: Privacy-preserving computations.
- Solidity: Smart contract development.
- Ethereum/Polygon: Blockchain networks.
- Hardhat: Smart contract development environment.
- Ethers.js: Blockchain interaction.
- React/Next.js: User interface framework.
- Web3.js/Ethers.js: Blockchain interactions.
- zkLogin: Secure, keyless access.
- MetaMask: Web3 authentication.
- Python 3.x
- Node.js & pnpm
- MongoDB
- MetaMask browser extension
# Clone the repository
git clone https://github.com/Njine/AthleteIQ
cd AthleteIQ
cd Backend
# Set up a virtual environment
python -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`
# Install dependencies
pip install -r requirements.txt
pyton app.py- Install depends
# Navigate to the frontend directory
cd Client
# Install dependencies
pnpm install- Run a local network in the first terminal:
pnpm chainThis command starts a local Ethereum network that runs on your local machine and can be used for testing and development. Learn how to customize your network configuration.
- On a second terminal, deploy the test contract:
pnpm deployThis command deploys a test smart contract to the local network. You can find more information about how to customize your contract and deployment script in our documentation.
- On a third terminal, start your NextJS app:
pnpm startVisit your app on: http://localhost:3000.
| Week | Task |
|---|---|
| 1-2 | MVP planning, setup, and environment configuration |
| 3-4 | Smart contract development and testnet deployment |
| 5 | Backend & frontend integration |
| 6 | AI/ML integration for performance analysis |
| 7 | Testing and debugging |
| 8 | UI/UX polish and final demo preparation |
- Smart Contracts: Deployed on a testnet (e.g., Goerli, Polygon Mumbai).
- Frontend: Fully functional Next.js interface.
- Backend: Flask API for data processing and AI integration.
- AI/ML Models: Performance analytics and insights.
- Demo Video & Presentation: Showcasing the dApp’s features.
- Advanced Analytics: More AI-powered insights for training optimization.
- Sponsorship Platform: Integration with sponsors for branded rewards.
- Community Features: Decentralized athlete collaboration.
- Governance: Token-based voting for platform upgrades.
Copyright (C) 2024 Licensed under the GPLv3 License