Python
Machine Learning and Django
2026
ID: 1CP0644
Carbon Footprint Prediction Using Advanced Machine Learning Techniques for Sustainability
Keywords:
Carbon
Footprint,
Machine
Learning,
Carbon
Emission
Prediction,
Sustainability,
Greenhouse
Gases,
Environmental
Monitoring.
Project Synopsis & Overview
Carbon Footprint Prediction Using Advanced Machine Learning Techniques for Sustainability aims to predict greenhouse gas emissions based on energy consumption, transportation, fuel usage, and lifestyle activities. Machine learning algorithms such as Random Forest, Decision Tree, and XGBoost analyze historical data to estimate carbon emissions. The system identifies major emission sources, visualizes trends, and supports sustainable decisions to reduce environmental impact and promote a greener future.
Complete Technical Specifications
| Project ID | 1CP0644 (DB ID: 644) |
| Project Title | Carbon Footprint Prediction Using Advanced Machine Learning Techniques for Sustainability |
| Domain Division | Python |
| Sub-Domain / Tech | Machine Learning and Django |
| IEEE Year | 2026 |
| Package Price | ₹6500 |
| Created Date | Oct 23, 2026 |
Project Price
₹6500
₹8000
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100% Executable Source Code & DB
IEEE Journal Paper Synopsis & PPT
1-on-1 AnyDesk/Zoom Live Setup Support
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