CarbonInsight Backend

A comprehensive Django REST API for tracking and analyzing carbon emissions across supply chains, with support for Asset Administration Shell (AAS) standards and digital product passports.

🌐 Live Demo: https://www.carboninsight.strahilpeykov.com/

Overview

CarbonInsight helps companies track, calculate, and reduce their carbon footprint across complex supply chains. Built for SMEs who need accessible tools for Product Carbon Footprint (PCF) calculations and Digital Product Passport (DPP) creation using open standards like Asset Administration Shell (AAS).

Features

• Supply Chain Emissions Tracking: Track carbon emissions across complex product Bill of Materials (BoM)
• Multiple Emission Types: Support for transport, production energy, and user energy emissions
• Standards Compliance: Export to Asset Administration Shell (AAS) formats (AASX, XML, JSON)
• SCSN Integration: Export Product Carbon Footprint data in SCSN XML format
• Company & Product Management: Multi-tenant architecture with company-based product ownership
• Data Sharing: Request and approve access to supplier emission data
• Import/Export: Bulk import/export via CSV, XLSX, and standardized formats
• AI Recommendations: OpenAI-powered suggestions for emission reduction
• Audit Logging: Complete audit trail of all changes
• Authentication: JWT-based authentication with rate limiting

Tech Stack

• Backend: Django 5.0, Django REST Framework
• Database: PostgreSQL (production), SQLite (development)
• Authentication: JWT tokens with SimpleJWT
• Standards: AAS (Asset Administration Shell), SCSN (Smart Connected Supplier Network)
• AI: OpenAI integration for recommendations
• Deployment: Railway.app, Vercel compatible

Architecture

Core Models

• Company: Organizations that own products and manage users
• Product: Items with associated emissions and Bill of Materials
• Emission: Abstract base for different emission types:
  • TransportEmission: Shipping and logistics emissions
  • ProductionEnergyEmission: Manufacturing energy consumption
  • UserEnergyEmission: End-user energy consumption
• ProductBoMLineItem: Bill of Materials relationships between products
• ProductSharingRequest: Mechanism for requesting access to supplier emission data

Getting Started

Prerequisites

• Python 3.12+
• PostgreSQL (for production) or SQLite (for development)
• pip for package management

Installation

1. Clone the repository

   git clone https://github.com/StrahilPeykov/carboninsight-backend.git
   cd carboninsight-backend

2. Install dependencies

   pip install -r requirements.txt

3. Environment setup

   # Copy and configure environment variables
   export DJANGO_SECRET_KEY="your-secret-key"
   export DATABASE_URL="your-database-url"  # Optional for production
   export OPENAI_API_KEY="your-openai-key"  # Optional for AI features

4. Database setup

   cd CarbonInsight
   python manage.py migrate

5. Create superuser (optional)

   python manage.py createsuperuser

Running the Server

cd CarbonInsight
python manage.py runserver

The API will be available at http://localhost:8000

Quick Setup with Test Data

# Populate database with sample companies, users, and products
POST http://localhost:8000/api/populate_db/
# Login: [email protected] / 1234567890

# Clean database when needed
POST http://localhost:8000/api/destroy_db/

API Documentation

• Swagger UI: http://localhost:8000/api/schema/swagger-ui/
• ReDoc: http://localhost:8000/api/schema/redoc/
• OpenAPI Schema: http://localhost:8000/api/schema/

Testing

cd CarbonInsight
python manage.py test

# With coverage
coverage run --source='.' manage.py test
coverage report
coverage html

Deployment

Railway.app (Current)

The project is configured for Railway deployment with automatic deployment from the main branch.

Manual Deployment

pip install -r requirements.txt
cd CarbonInsight
python manage.py collectstatic --noinput
python manage.py migrate
gunicorn CarbonInsight.wsgi:application --bind 0.0.0.0:8000

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for new functionality
5. Ensure all tests pass (python manage.py test)
6. Commit your changes (git commit -m 'Add amazing feature')
7. Push to the branch (git push origin feature/amazing-feature)
8. Open a Pull Request

Environment Variables

Variable	Description	Default
DJANGO_SECRET_KEY	Django secret key	Auto-generated
DATABASE_URL	PostgreSQL connection string	SQLite (dev)
OPENAI_API_KEY	OpenAI API key for AI features	None
RAILWAY_ENVIRONMENT_NAME	Railway deployment environment	None
FRONTEND_DOMAIN	Frontend domain for CORS	localhost:3000

Standards Compliance

Asset Administration Shell (AAS)

• Full AAS Digital Nameplate submodel support
• Product Carbon Footprint submodel compliance
• Export to AASX, XML, and JSON formats

SCSN (Supply Chain Sustainability Network)

• UBL-compliant XML export
• Product Carbon Footprint data exchange
• Bill of Materials representation

License

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

Acknowledgments

• Built in collaboration with Brainport Industries & TU Eindhoven
• Supports Dutch government and European Commission initiatives for Digital Product Passports
• Implements OPC Foundation Asset Administration Shell standards

Contact

• Author: Strahil Peykov
• Live Demo: https://www.carboninsight.strahilpeykov.com/
• Issues: GitHub Issues

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Empowering SMEs to create sustainable supply chains through accessible carbon footprint tracking and standards-compliant digital product passports.