Carbon Tracker is a web application that helps users track their food choices and understand the carbon emissions associated with them.
The goal is to encourage sustainable eating habits by providing personalized insights and history tracking.

🔗 Live Demo (if hosted)

• Allows users to create a personal profile.
• Log food items and calculate their carbon footprint instantly.
• Visualize history and insights with clean charts.
• Promote awareness of how dietary choices impact the environment.

Climate change is one of the biggest challenges of our time. Food production contributes to a significant share of greenhouse gas emissions. However, most people are unaware of the emissions tied to their daily meals.
Carbon Tracker bridges this gap by making food emissions transparent, simple, and engaging to track.

• Uses a carbon emissions dataset for foods.
• Applies data cleaning, processing, and analysis with Python (pandas, NumPy, scikit-learn).
• Offers predictive insights into user trends over time.
• Future plans include integrating AI recommendations for eco-friendly alternatives.

By helping individuals become aware of the carbon footprint of their diet:

• Encourages sustainable food choices.
• Contributes to reducing overall emissions.
• Scales awareness from individuals to collective climate action.

Frontend

• HTML5, CSS3, Bootstrap 5 (Dark Theme)
• Jinja2 Templates (Flask Integration)

Backend

• Flask (Python)
• MongoDB (Data Storage)

Data & Visualization

• NumPy, pandas (Data Handling)
• Matplotlib, Seaborn (Visualizations)

carbon-tracker/ │── app.py # Main Flask Application │── templates/ # Jinja2 HTML Templates │ ├── base.html │ ├── index.html │ ├── profile.html │ ├── history.html │── static/ # CSS, JS, Images │── requirements.txt # Dependencies │── README.md # Documentation

yaml Copy Edit

1. Clone the repository

   git clone https://github.com/your-username/carbon-tracker.git
   cd carbon-tracker

python -m venv venv
source venv/bin/activate  # For Mac/Linux
venv\Scripts\activate     # For Windows

pip install -r requirements.txt

flask run : python app.py
Visit:
👉 http://127.0.0.1:5000/

✅ Add AI-based recommendations for low-emission meal alternatives.
✅ Enhance visualization with interactive dashboards.
✅ Mobile-first responsive design.
✅ Integration with fitness & diet APIs.

1 - Backend => Ahmad (Me)
2 - Frontend => M.AizazUllah

This project is licensed under the MIT License.