🌱 Carbon Footprint Tracker for Indian Households

A comprehensive Django web application designed specifically for Indian households to track, analyze, and reduce their carbon footprint. Built with Bootstrap 5, Chart.js, and featuring India-specific emission factors and data sources.

🇮🇳 India-Centric Features

• Local Emission Factors: Uses India-specific emission factors for electricity, fuels, and food
• Indian Fuel Prices: Real-time scraping of petrol, diesel, LPG, and electricity prices by state
• Indian Diet Analysis: Tailored for Indian cuisine patterns (vegetarian, non-vegetarian, regional variations)
• Multi-language Support: Ready for Hindi and regional language integration
• Indian Currency: All pricing in Indian Rupees (₹)
• State-wise Data: Supports all Indian states with location-specific calculations

✨ Key Features

📊 Comprehensive Tracking

• Energy Usage: Electricity, LPG, CNG, Kerosene, Wood/Biomass, Coal, Solar
• Transportation: All modes from bicycles to international flights
• Diet & Food: Indian diet patterns with food waste tracking
• Emission Calculations: Automatic CO₂ calculations with Indian emission factors

🎨 Modern UI/UX

• Bootstrap 5: Responsive, mobile-first design
• Indian Theme: Saffron, green, and white color scheme
• Interactive Charts: Chart.js visualizations with emission breakdowns
• Dark/Light Mode: User preference support (planned)

🔧 Technical Features

• Django 4.2+: Modern Python web framework
• REST API: Full API access for mobile apps and integrations
• Web Scraping: BeautifulSoup integration for real-time price data
• Database: SQLite (development) / PostgreSQL (production ready)
• Authentication: Django's built-in user system with household profiles

📈 Analytics & Insights

• Monthly Trends: Track emission changes over time
• Category Breakdown: Detailed analysis by energy, transport, and diet
• National Comparisons: Compare with Indian national averages
• Goal Setting: Personal reduction targets and progress tracking
• Eco Tips: Curated suggestions for reducing carbon footprint

🚀 Quick Start

Prerequisites

• Python 3.8+ installed
• pip package manager
• Git (for cloning)

Installation

1. Clone the repository

git clone <repository-url>
cd carbontrack

2. Create virtual environment

python3 -m venv carbon_env
source carbon_env/bin/activate  # On Windows: carbon_env\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Setup database

python manage.py makemigrations
python manage.py migrate

5. Create superuser (optional)

python manage.py createsuperuser

6. Load initial data

python manage.py shell
>>> from tracker.scraper import run_all_scrapers
>>> run_all_scrapers()  # Load sample fuel prices and eco tips
>>> exit()

7. Run development server

python manage.py runserver

8. Access the application
   • Main app: http://127.0.0.1:8000/
   • Admin panel: http://127.0.0.1:8000/admin/
   • API docs: http://127.0.0.1:8000/api/

📱 Usage Guide

Getting Started

1. Register: Create a new account on the homepage
2. Setup Household: Complete your family profile with location and member count
3. Start Tracking: Begin adding your energy, transport, and diet data
4. View Dashboard: Monitor your emissions and progress

Adding Data

Energy Usage

• Go to "Add Data" → "Energy Usage"
• Select energy source (electricity, LPG, etc.)
• Enter consumption amount and period
• System automatically calculates CO₂ emissions

Transportation

• Select transport mode (bike, car, bus, train, flight)
• Enter distance and frequency
• Add fuel costs if available
• Get emission breakdown by transport type

Diet & Food

• Choose your diet pattern (vegan, vegetarian, non-veg)
• Set frequency of different food types
• Estimate food waste percentage
• See impact of dietary choices

Viewing Reports

• Dashboard: Current month overview with trends
• Reports: Detailed yearly analysis and comparisons
• Charts: Interactive visualizations of your data
• Tips: Personalized recommendations for reduction

🛠️ Development

Project Structure

carbontrack/
├── carbontrack/          # Django project settings
├── tracker/              # Main application
│   ├── models.py        # Database models
│   ├── views.py         # View logic
│   ├── serializers.py   # API serializers
│   ├── scraper.py       # Web scraping functionality
│   └── admin.py         # Admin interface
├── templates/           # HTML templates
│   ├── base.html       # Base template
│   └── tracker/        # App-specific templates
├── static/             # Static files
│   ├── css/           # Stylesheets
│   ├── js/            # JavaScript
│   └── img/           # Images
├── requirements.txt    # Python dependencies
└── manage.py          # Django management script

Key Models

• Household: User family/household information
• EnergyUsage: Energy consumption tracking
• TransportUsage: Transportation emission data
• DietEmission: Food-related emissions
• MonthlyEmissionSummary: Aggregated monthly data
• EcoTip: Environmental tips and suggestions
• FuelPrice: Current fuel prices by state

API Endpoints

/api/households/              # Household management
/api/energy-usage/            # Energy data CRUD
/api/transport-usage/         # Transport data CRUD
/api/diet-emissions/          # Diet data CRUD
/api/monthly-summaries/       # Emission summaries
/api/eco-tips/               # Environmental tips
/api/update-data/            # Trigger data scraping

Customization

Adding New Emission Factors

# In Django shell or data migration
from tracker.models import EmissionFactor

EmissionFactor.objects.create(
    category='energy',
    name='Solar Panel',
    unit='kWh',
    emission_factor=0.05,  # kg CO2 per kWh
    source='Renewable Energy Agency'
)

Modifying Calculations

Edit the calculate_emissions() methods in models.py for each category:

• EnergyUsage.calculate_emissions()
• TransportUsage.calculate_emissions()
• DietEmission.calculate_emissions()

Adding New States

from tracker.models import IndianState

IndianState.objects.create(
    name='Goa',
    electricity_emission_factor=0.78  # kg CO2/kWh
)

🌐 Deployment

Production Setup

1. Environment Variables

export DEBUG=False
export SECRET_KEY='your-secret-key'
export DATABASE_URL='postgresql://user:password@host:port/dbname'
export ALLOWED_HOSTS='yourdomain.com,www.yourdomain.com'

2. Database (PostgreSQL)

pip install psycopg2-binary
# Update DATABASES in settings.py
python manage.py migrate

3. Static Files

python manage.py collectstatic

4. Web Server (Nginx + Gunicorn)

pip install gunicorn
gunicorn carbontrack.wsgi:application --bind 0.0.0.0:8000

Docker Deployment

FROM python:3.11-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt

COPY . .
RUN python manage.py collectstatic --noinput

EXPOSE 8000
CMD ["gunicorn", "carbontrack.wsgi:application", "--bind", "0.0.0.0:8000"]

Heroku Deployment

1. Create Procfile:

web: gunicorn carbontrack.wsgi:application
release: python manage.py migrate

2. Update requirements.txt with production dependencies
3. Configure environment variables in Heroku dashboard
4. Deploy using Git or Heroku CLI

🔧 Configuration

Settings Options

# Custom settings in carbontrack/settings.py

# Carbon footprint specific settings
CARBON_FOOTPRINT_SETTINGS = {
    'DEFAULT_EMISSION_FACTORS': {
        'electricity': 0.82,  # kg CO2/kWh for India
        'lpg': 2.98,          # kg CO2/kg
        'petrol': 2.31,       # kg CO2/litre
        'diesel': 2.68,       # kg CO2/litre
    },
    'AVERAGE_INDIAN_EMISSIONS': {
        'per_capita_yearly': 1900,  # kg CO2 per person per year
        'household_monthly': 300,   # kg CO2 per household per month
    }
}

# Celery for background tasks (optional)
CELERY_BROKER_URL = 'redis://localhost:6379/0'
CELERY_RESULT_BACKEND = 'redis://localhost:6379/0'

Web Scraping Configuration

The app includes BeautifulSoup-based scrapers for:

• Fuel prices from Indian petroleum websites
• Eco tips from environmental websites
• Electricity tariffs from state electricity boards

To run scrapers manually:

from tracker.scraper import run_all_scrapers
run_all_scrapers()

🧪 Testing

Run Tests

python manage.py test

Test Coverage

pip install coverage
coverage run --source='.' manage.py test
coverage report
coverage html  # Generate HTML report

Sample Data for Testing

# In Django shell
from django.contrib.auth.models import User
from tracker.models import Household, IndianState

# Create test user and household
user = User.objects.create_user('testuser', 'test@example.com', 'password')
state = IndianState.objects.create(name='Delhi', electricity_emission_factor=0.82)
household = Household.objects.create(
    user=user,
    name='Test Family',
    house_type='apartment',
    members_count=4,
    state=state,
    city='New Delhi'
)

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Workflow

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Make changes and test thoroughly
4. Commit changes: git commit -m "Add feature"
5. Push to branch: git push origin feature-name
6. Create a Pull Request

Code Style

• Follow PEP 8 for Python code
• Use meaningful variable and function names
• Add docstrings for all functions and classes
• Write tests for new features

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Indian Government: For emission factor data and environmental policies
• Bootstrap Team: For the excellent CSS framework
• Chart.js: For beautiful, responsive charts
• Django Community: For the robust web framework
• Environmental Organizations: For guidance on carbon footprint calculations

📞 Support

• Issues: Report bugs and request features on GitHub Issues
• Email: contact@ecotrack-india.com
• Documentation: Full API docs available at /api/
• Community: Join our Discord server for discussions

🗺️ Roadmap

Upcoming Features

• Mobile app (React Native)
• Hindi and regional language support
• Advanced analytics with ML predictions
• Community challenges and leaderboards
• Integration with smart home devices
• Carbon offset marketplace
• Export data to PDF reports
• Social sharing of achievements

Version History

• v1.0.0: Initial release with core tracking features
• v1.1.0: Web scraping and real-time price updates
• v1.2.0: Advanced visualizations and comparisons
• v2.0.0: Mobile app and API v2 (planned)

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Made with ❤️ in India for a sustainable future 🌍

Contribute to reducing India's carbon footprint, one household at a time.