This utility provides a web interface and RESTful API for anomaly detection functionality.
The web interface, served with a Node.js container, establishes a connection to the C++ server container, which holds the detection functionality. It communicates with the server to retrieve the necessary information for the user.
The C++ server is located in the cppDetectionServer folder. The web server files can be found in the rest of the project. The main server file is src/index.js. The HTML files served (using EJS) are stored in the views folder, adhering to the MVC architecture.
The project is divided into two containers: Backend: The C++ server that contains the algorithms. Frontend: The Node.js server that serves the web interface and handles requests.
To run the project, you need to have Docker installed and started on your machine.
Open the terminal inside the project folder and run the following command: docker-compose up -d.
After starting the web server, you can access it through a web browser using the following URL:
localhost:8080
In the web interface, you can select an algorithm, upload training and detection CSV files, and click "Start" to begin the anomaly detection process.
The main entry point for the RESTful API is the following URL (using the POST method):
localhost:8080
You need to supply a JSON object in the following format:
{
"alg": "Regression algorithm/Hybrid algorithm",
"trainData": "...",
"detectData": "..."
}Make sure to replace trainData and detectData with the actual data (not file names). The API will return a JSON object that contains the anomalies.
