Tokenized Realty - A Decentralized Platform for Fractional Property Ownership
Welcome to Tokenized Realty, a decentralized platform combining blockchain technology and machine learning to democratize real estate investments. This project addresses challenges like high costs, lack of transparency, and limited accessibility by enabling fractional ownership and real-time property price predictions.
- Fractional Ownership: Securely buy and sell fractions of high-value properties using blockchain technology.
- Real-Time Price Predictions: Machine learning models predict property prices based on historical and market data.
- Smart Contracts: Automated ownership transfers and transactions using Ethereum-based ERC-721 tokens.
- Decentralized Marketplace: Trade tokenized real estate assets in a secure, transparent environment.
- Wallet Integration: Securely manage transactions using MetaMask.
- User-Friendly Interface: Intuitive design for a seamless experience, built with React.js.
- Ethereum Blockchain: Decentralized platform for secure token transactions.
- Smart Contracts: Developed using Solidity for ERC-721 tokens.
- ethers.js: Simplified interaction with the Ethereum blockchain.
- Hardhat: For testing and deploying smart contracts.
- OpenZeppelin: Secure contract library for reliable implementation.
- Models: Random Forest for price predictions with 90% accuracy.
- Libraries:
- scikit-learn: Training and evaluating ML models.
- Pandas: Data manipulation and analysis.
- Matplotlib: Visualizing property trends and market data.
- Frontend: React.js for an interactive user interface.
- Backend: Node.js and Express.js for handling API requests and business logic.
- Database: MongoDB for efficient and secure data storage.
- Flask: Integration of machine learning models for seamless predictions.
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Tokenization:
- Enter property details, and the platform generates ERC-20 tokens representing fractional ownership.
- Smart contracts ensure secure and transparent transactions.
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Price Prediction:
- Input property features, and the ML model provides accurate real-time price forecasts.
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Marketplace:
- Users can trade tokenized properties in a decentralized, secure digital environment.
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Wallet Integration:
- Transactions are securely managed using MetaMask.
- Prediction Accuracy: 90% for property prices.
- Transaction Transparency: 100% ensured via blockchain.
- Fractional Ownership: Investments as low as 1% per property.
/client # Frontend code (React.js)
/flask_server # Flask server for integrating ML models and price predictions
/smart_contract # Solidity smart contracts for ERC-721 tokenization
/server # Backend code for MongoDB integration, API services, and transaction handling
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Clone the repository:
git clone https://github.com/your-repo/tokenized-realty.git cd tokenized-realty -
Install dependencies for each component:
- Frontend (React.js):
cd client && npm install
- Flask Server (ML Integration):
cd flask_server && pip install -r requirements.txt
- Backend (Node.js, MongoDB):
cd server && npm install
- Frontend (React.js):
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Start the local blockchain using Hardhat:
npx hardhat node
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Deploy smart contracts:
npx hardhat run scripts/deploy.js --network localhost
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Start the Flask server for ML model integration:
cd flask_server && python app.py
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Start the backend server:
cd server && npm start
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Run the frontend application:
cd client && npm start
- Ayush Talan: Blockchain development and ERC-20 smart contracts.
- Saumya Sharma(https://github.com/saumyasharma03): Blockchain integration with backend and transaction validation.
- Saurabh Pandey(https://github.com/Pandey-SaurabhP): Real-time ML model optimization and API development.
- Aryav Singla(https://github.com/Slemon30): Data collection, preprocessing, and ML model training.
Tokenized Realty brings innovation to real estate by making investments more accessible, efficient, and inclusive. By leveraging blockchain for transparency and ML for insightful predictions, this platform aims to revolutionize property transactions and empower investors globally.
Feel free to explore and contribute to this project! For any queries or feedback, please open an issue or reach out. 🌟