The AI Powered Performance Analyzer is a sophisticated system monitoring tool designed to track real-time system metrics, detect process anomalies using machine learning, and forecast future resource usage. Built with a robust Python backend and a modern, responsive frontend, it provides deep insights into system performance.
- Real-Time Monitoring: Live tracking of CPU, Memory, Threads, and Disk I/O for all active processes.
- AI-Driven Anomaly Detection: Utilizes an Isolation Forest model to identify suspicious or abnormal process behavior in real-time.
- Predictive Forecasting: Implements Random Forest Regressors to predict future system resource consumption (CPU & Memory).
- Interactive Dashboard: A dark-themed, responsive web interface featuring:
- Live charts for current and forecasted usage.
- Searchable and filterable process table (User vs. System processes).
- Real-time anomaly log stream.
- Data Export: Ability to export anomaly logs to CSV for further analysis.
- Backend: Python, Flask
- System Interaction: Psutil
- Machine Learning: Scikit-learn (Isolation Forest, Random Forest), Pandas, NumPy, Joblib
- Frontend: HTML5, CSS3 (Custom Properties, Glassmorphism), JavaScript (Vanilla)
- Python 3.8 or higher
- pip (Python Package Manager)
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Clone the Repository
git clone <repository-url> cd <repository-directory>
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Install Dependencies
pip install flask pandas numpy scikit-learn psutil joblib
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Run the Application
python server.py
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Access the Dashboard Open your web browser and navigate to:
http://localhost:5000
This project was developed by:
- Mayank Bansal - https://www.linkedin.com/in/mayank-bansal14/
- Surya Narayan Battula - https://www.linkedin.com/in/suryanarayanbattula/
- Lukshya Supyal - https://www.linkedin.com/in/lukshya-supyal2006/