CarbonCare is an AI-powered platform that helps logistics businesses optimize their operations for sustainability. Through advanced analytics and machine learning, it provides actionable insights to reduce carbon footprint, improve resource efficiency, and make supply chains more environmentally friendly.
- Real-time Sustainability Analytics: Monitor key metrics like carbon emissions, resource utilization, and energy efficiency
- AI-powered Insights: Get actionable recommendations from our ML model to improve sustainability scores
- Interactive Dashboard: Visualize sustainability data through intuitive charts and metrics
- Predictive Analytics: Forecast environmental impact and optimize future shipments
- Batch Analysis: Process multiple shipments to identify patterns and optimization opportunities
- Python 3.8+
- Node.js 15+
- React 18+
- PostgreSQL with Supabase
# Clone repository
git clone https://github.com/yourusername/carboncare.git
# Enter server directory
cd carboncare/server
# Create virtual environment
python -m venv venv
source venv/bin/activate # or `venv\Scripts\activate` on Windows
# Install dependencies
pip install -r requirements.txt
# Start server
python [app.py](http://_vscodecontentref_/0)# Enter client directory
cd ../client
# Install dependencies
npm install
# Start development server
npm run dev
Frontend: Next.js, Tailwind CSS, Recharts Backend: Flask, scikit-learn, LangChain Database: PostgreSQL (Supabase) ML Model: Random Forest for sustainability prediction API: RESTful endpoints with JWT authentication
The platform analyzes several key sustainability metrics:
Package Sustainability Index (PSI)
Route Efficiency Score (RES)
Carbon Emission Index (CEI)
Resource Utilization Rate (RUR)
Energy Efficiency Rating (EER)
Waste Reduction Score (WRS)
JWT-based authentication Role-based access control Secure API endpoints Environment variable protection