Incentivized Factory Safety Monitoring Platform

A hackathon project that monitors factory working conditions and automatically rewards safe operations using Solana blockchain.

• Node.js 18+
• npm or yarn
• Python 3.11+ (for ML model)

# Install frontend + server dependencies
npm install

# Install ML dependencies
pip install -r requirements.txt

# Start development server
npm run dev

The app will open at http://localhost:3000

Arduino --> Express Server --> ML API --> Risk Score --> Solana Reward
               |                  |             |
           Snowflake          Snowflake      Snowflake
        (raw readings)    (compliance scores) (reward txns)

• Hardware: Arduino Nano 33 BLE Sense (temperature, humidity, pressure, proximity, vibration, noise)
• ML Model: LSTM Autoencoder for anomaly detection + risk scoring (Python/PyTorch)
• ML API: FastAPI bridge wrapping trained model (src/api.py)
• Backend: Express server receiving sensor data, querying ML, distributing rewards (server/index.js)
• Frontend: React + TypeScript + Vite dashboard
• Blockchain: Solana devnet for automated reward payouts
• Data Warehouse: Snowflake (6 schemas, 30+ features) for analytics, compliance scoring, and governance

1. Safety Monitoring Dashboard

   • Real-time environmental metrics (temperature, humidity, air quality, noise, lighting)
   • Safety score calculation (0-100)
   • Multi-factory support

2. ML-Powered Risk Detection

   • LSTM autoencoder trained on ~57k rows of environmental data
   • Anomaly detection + OSHA threshold violation scoring
   • Risk index: 0-100 (Safe / Caution / Warning / Critical)

3. Automated Reward System

   • SOL transfers to factories when risk score < 0.3
   • Reward amount scales with safety score (0.1-0.2 SOL)
   • On-chain compliance record storage

4. Snowflake Data Warehouse

   • Automated ETL pipeline (Streams + Tasks DAG)
   • Cortex ML anomaly detection + forecasting
   • Cortex LLM-powered compliance reports
   • RBAC, data masking, row access policies
   • Secure data sharing for regulators/NGOs

5. Wallet Integration

   • Connect wallet (demo mode with local storage)
   • View balance and transaction history
   • Send rewards directly from the dashboard

SafeShift/
├── src/                        # ML model + React frontend
│   ├── model.py               # LSTM Autoencoder
│   ├── preprocess.py          # Data preprocessing pipeline
│   ├── train.py               # Model training
│   ├── api.py                 # FastAPI ML bridge
│   ├── nlp.py                 # NLP verbal abuse detection
│   ├── components/            # React components
│   ├── services/              # Solana reward services
│   └── context/               # React context
├── server/                     # Express backend
│   └── index.js               # API server + reward distribution
├── snowflake/                  # Snowflake data warehouse
│   ├── 00-08_*.sql            # Individual setup scripts
│   ├── 09_test_validation.sql # Validation tests
│   └── RUN_ALL.sql            # Single deployment script
├── models/                     # Trained ML artifacts
├── config/                     # Safety thresholds + wallet config
├── data/                       # Training datasets
├── docs/                       # Documentation
├── ProximitySensor/            # Arduino proximity sensor
├── ReadPressure/               # Arduino pressure sensor
└── ArduinoToJson/              # Arduino JSON output

npm run dev          # Start frontend dev server
npm run build        # Build for production
npm run server       # Start Express backend
npm run dev:all      # Start frontend + backend concurrently

python -m src.api    # Start ML API (port 8000)
python -m src.train  # Train ML model

• See docs/context.md for full project context
• See docs/models.md for ML model architecture
• See docs/solana-and-model-logic.md for Solana integration
• See snowflake/RUN_ALL.sql for complete database deployment

ISC