⚡ Elektrum - Home Energy Dashboard

Where Energy Meets Intelligence

Real-time energy monitoring system with predictive analytics, room-wise consumption tracking, and smart billing integration for Sri Lankan homes.

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✨ Key Features

📊 Real-Time Monitoring

• Live power consumption tracking (Watts)
• Voltage and current monitoring
• Temperature & humidity sensors
• 5-second data refresh intervals
• 24-hour historical data

🏠 Room-Wise Analytics

• Individual room power consumption tracking
• Current (Amperes) and power (Watts) breakdown
• Average and peak power metrics
• Visual power distribution pie charts
• Room-specific consumption percentages

🤖 Predictive Analytics

• Ridge Regression time-series forecasting
• Consumption pattern analysis
• Daily/weekly/monthly trend predictions
• Real-time model status indicator

💡 Smart Reports & Billing

• PDF Report Generation: Weekly and monthly summaries
• Bill Integration: Quick links to CEB and LECO payment portals
• Cost Estimation: Daily, monthly cost calculations (₹13.06/kWh default)
• Carbon Tracking: Monthly CO₂ footprint calculations in kg

📈 Visualizations

• 24-hour usage pattern charts
• Power consumption by room (bar charts)
• Power distribution pie charts
• System status monitoring
• Real-time data points counter

🔌 Connected Systems

• MongoDB for historical data storage
• IoT sensor integration
• Active connection status indicator
• Scalable architecture

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🛠️ Tech Stack

Layer	Technology
Frontend	React, Tailwind CSS, Chart.js
Backend	FastAPI, Python
Database	MongoDB
IoT/Sensors	Real-time energy sensors
Data Processing	Ridge Regression, Time-series analysis
Deployment	Vercel & AWS EC2

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🚀 Quick Start

Prerequisites

• Node.js 16+
• Python 3.9+
• MongoDB instance
• IoT energy sensors/smart meters

Frontend Setup

# Install dependencies
npm install

# Start development server
npm start

# Build for production
npm run build

Backend Setup

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Start FastAPI server
uvicorn main:app --reload

Environment Variables

# Frontend (.env)
REACT_APP_API_URL=http://localhost:8000

# Backend (.env)
MONGODB_URI=mongodb://localhost:27017
DATABASE_NAME=elektrum
SENSOR_UPDATE_INTERVAL=5

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📋 Project Structure

elektrum/
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   │   ├── Dashboard.jsx
│   │   │   ├── RoomConsumption.jsx
│   │   │   ├── Charts.jsx
│   │   │   └── BillPayment.jsx
│   │   ├── pages/
│   │   └── App.jsx
│   └── package.json
├── backend/
│   ├── main.py
│   ├── models/
│   │   ├── sensor.py
│   │   └── room.py
│   ├── routes/
│   │   ├── energy.py
│   │   ├── analytics.py
│   │   └── reports.py
│   ├── services/
│   │   ├── prediction.py
│   │   └── pdf_generator.py
│   └── requirements.txt
└── README.md

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🎮 Usage

View Real-Time Metrics

• Dashboard displays live power consumption, voltage, temperature, and humidity
• Auto-refreshes every 5 seconds
• Filter data by time range (1h, 6h, 24h, 7d)

Monitor Room Consumption

• Check individual room power usage
• Compare current, average, and peak consumption
• Identify high-usage rooms instantly

Generate Reports

• Click "Weekly Report" or "Monthly Report"
• Includes consumption breakdown, daily stats, costs, and carbon footprint
• PDFs ready for download

Pay Bills

• Quick links to CEB (Ceylon Electricity Board) and LECO payment portals
• Estimated monthly bill based on consumption
• Accurate rate calculations

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📊 Predictions & Analytics

The system uses Ridge Regression for time-series forecasting:

• Analyzes historical consumption patterns
• Predicts future energy usage
• Helps identify optimization opportunities
• Real-time model status display

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🌍 Sri Lanka Specific Features

• Billing Integration: Direct links to CEB and LECO portals
• Local Pricing: Default rate ₹13.06/kWh (configurable)
• Carbon Footprint: Monthly CO₂ tracking in kg
• Multi-Language Support: Ready for Sinhala/Tamil translation

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📈 API Endpoints

Energy Data

• GET /api/energy/current - Current power metrics
• GET /api/energy/history?room=&range=24h - Historical data
• POST /api/energy/log - Log sensor reading

Analytics

• GET /api/analytics/predict?days=7 - Predict next 7 days
• GET /api/analytics/patterns - Get consumption patterns
• GET /api/analytics/carbon-footprint - Monthly CO₂ data

Reports

• POST /api/reports/generate?type=weekly - Generate PDF
• GET /api/reports/estimated-bill - Calculate estimated cost

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🔮 Future Enhancements

• Smart device integration (IoT appliance control)
• Mobile app (React Native/Flutter)
• Machine learning optimization suggestions
• Solar panel integration & off-grid monitoring
• Automated alerts for peak usage
• Multi-home support
• Advanced anomaly detection
• Dark mode UI

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📝 License

MIT License - Feel free to use, modify, and distribute

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🤝 Contributing

Contributions welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit changes (git commit -m 'Add AmazingFeature')
4. Push to branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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📧 Contact & Support

• Issues: Open a GitHub issue for bugs and feature requests
• Email: kavix@yahoo.com
• Live Demo: https://cd-kavindu.vercel.app/

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🎯 Status

🚀 Active Development - v1.0.0 Released

• ✅ Core dashboard functionality
• ✅ Room-wise monitoring
• ✅ Predictive analytics
• ✅ PDF report generation
• ⏳ Mobile app in progress
• ⏳ Advanced ML features

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⚡ Monitor. Predict. Optimize. Save.