AI-Powered Anomaly Detection System for IoT Networks

Project Description

The AI-powered Anomaly Detection System for IoT Networks is designed to monitor data from various IoT devices in real-time to identify and alert on any anomalies that could indicate security threats or malfunctions. This system leverages machine learning to detect unusual patterns or behaviors, providing actionable insights to maintain the health and security of the IoT network.

Project Features

• Real-Time Monitoring: Continuously monitor data streams from IoT devices.
• Anomaly Detection: Use machine learning models to detect deviations from normal behavior.
• Alerts and Notifications: Send alerts and notifications when anomalies are detected.

Future Enhancements

• Analytics Dashboard: Provide a dashboard for viewing alerts, device statuses, and historical data.
• Device Management: Maintain a registry of connected devices and their statuses.
• Enhanced Anomaly Detection: Implement more advanced anomaly detection algorithms.
• Integration with External Systems: Integrate with third-party APIs for enhanced functionality.

Prerequisites

1. Programming Skills: Proficiency in JavaScript and familiarity with Node.js.
2. Web Framework Knowledge: Understanding of Express.js for building APIs.
3. Database Management: Knowledge of MongoDB for storing data.
4. Machine Learning Basics: Understanding of machine learning concepts and tools.
5. IoT Basics: Basic knowledge of IoT devices and data communication protocols.

Technologies and Tools

• Node.js: Server-side JavaScript runtime.
• Express.js: Web framework for building APIs.
• MongoDB: NoSQL database for storing device data and anomaly reports.
• Socket.io: For real-time data communication.
• Machine Learning Libraries: TensorFlow.js or scikit-learn (Python backend).
• Docker: For containerization of applications.
• Grafana or Kibana: For visualizing analytics and monitoring data.

How to Run the Code

1. Clone the repository:

   git clone https://github.com/your-username/AI-IoT-Anomaly-Detector.git
   

2. Navigate into the project directory:

   cd AI-IoT-Anomaly-Detector
   

3. Install dependencies:

   npm install
   

4. Start the development server:

   npm start
   

5. Open http://localhost:5173 in your browser to access the anomaly detection system.

How to Contribute

Contributions are welcome! Here's how you can contribute to this project:

• Fork the repository
• Create a new branch for your feature or bug fix
• Make your changes and commit them
• Push your changes to your fork
• Submit a pull request

License

This project is licensed under the MIT License.

Screenshots