Smart Energy Optimizer predicts energy consumption based on real-time data (temperature, humidity, time of day) and suggests actions to optimize energy usage. It can be used for residential or industrial setups with IoT integration.
- Predicts energy consumption using machine learning.
- Real-time simulation with IoT data emulation.
- Energy-saving suggestions.
- Visualization of prediction accuracy.
- Python
- Scikit-Learn
- Pandas, NumPy
- Matplotlib
- Schedule
smart-energy-optimizer/ ├── data/ │ └── energy_data.csv # Sample dataset ├── models/ │ └── energy_optimizer_model.pkl # Trained model ├── scripts/ │ └── main.py # Core script for training and simulation ├── README.md ├── requirements.txt # Python dependencies └── LICENSE # License file (optional)
- Clone the repository:
git clone https://github.com/<username>/smart-energy-optimizer.git cd smart-energy-optimizer