Energy Consumption Optimization

Overview

The Energy Consumption Optimization part aims to monitor and optimize energy usage in the house. It provides real-time analytics, anomaly detection, and predictive modeling to help users manage their energy consumption effectively.

Features

• Real-time energy monitoring
• Anomaly detection for devices
• Historical data analysis
• Energy consumption forecasting
• Scheduling of tasks for energy optimization
• User-friendly web dashboard
• Daily cloud backup to Firebase at midnight

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python 3.7 or higher
• SQLite3
• Flask
• Pandas
• Prophet
• PyFlink

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/Energy-Consumption-Optimization.git
   cd Energy-Consumption-Optimization

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

4. Set up the database:

   • Run the database setup script to create the necessary tables:

   python database/create_database.py

5. Configure environment variables:

   • Create a .env file in the root directory and add the following variables:

   SMTP_SERVER_HOST=smtp.your-email-provider.com
   SMTP_SERVER_USERNAME=your_email@example.com
   SMTP_SERVER_PASSWORD=your_email_password
   
   # Set this to your project's root directory path
   ROOT_PATH=/path/to/your/Energy-Consumption-Optimization
   
   # Firebase credentials
   FIREBASE_API_KEY=your_firebase_api_key
   FIREBASE_AUTH_DOMAIN=your-project.firebaseapp.com
   FIREBASE_PROJECT_ID=your-project-id
   FIREBASE_STORAGE_BUCKET=your-project.appspot.com
   FIREBASE_MESSAGING_SENDER_ID=your_sender_id
   FIREBASE_APP_ID=your_app_id
   

Running the Application

The application requires multiple components to be running simultaneously in separate terminals:

1. Start the anomaly monitoring system:

   python anomaly_monitor.py

2. Start the real-time data generation (for simulating data receive) :

   python database/generate_real_time_data.py

3. Start the Flask application:

   python app.py

4. Access the dashboard:

   • Open your web browser and go to link.

Note: All three components (anomaly monitor, data generation, and Flask app) must be running simultaneously for the system to function properly. Each should be run in its own dedicated terminal window.

Usage

• Use the dashboard to monitor real-time energy consumption.
• Set up scheduled tasks for devices to optimize energy usage.
• Review historical data and predictions to make informed decisions.
• All data is automatically backed up to Firebase cloud storage at midnight each day.