The GreenML Dashboard is a sustainable AI initiative that leverages machine learning and green computing to accurately predict household appliance energy consumption based on indoor and outdoor environmental conditions such as temperature, humidity, occupancy, and CO₂ levels.
What sets this project apart is its integration with the
codecarbonlibrary to track the carbon emissions produced during model training, promoting eco-conscious AI practices.
- Python – Data handling and model development
- scikit-learn – ML algorithms (Linear Regression, Random Forest)
- codecarbon – Carbon footprint measurement
- seaborn & matplotlib – Visual analytics
- Streamlit – Interactive web dashboard
✅ Model performance comparison (MAE, R², CO₂ emissions)
✅ Heatmap showing top 10 feature correlations
✅ Single input prediction and batch CSV-based predictions
✅ Energy usage and environmental impact visualizations
✅ Streamlit-powered UI – ready for public deployment
- Clone the repo
- Run 'python preprocess.py'
- Run
streamlit run app.py