TCP-Connection

Simple TCP Connection with GUI (Patient Monitor)

TCP Connection with GUI (Patient Monitor)

This project implements a patient monitoring system using TCP/IP communication for data transmission and a Qt-based graphical user interface for real-time visualization.

Features

Client (Sender)

• Sending Vital Signs: Sends patient’s live vital signs to the server using TCP connection.
  • Ensure DEST_IP = "Ahmed" is set to your PC's localhost.
  • Connects client socket to the server specified by the destination IP and port.
• Patient Class: Defines a Patient class with attributes such as id, name, age, heart rate, systolic blood pressure, and diastolic blood pressure.
  • generate_vital_signs(): Generates random vital signs for a patient.
  • get_vital_signs(): Returns vital signs in JSON format.
• Client Send Function: Sends vital signs data in JSON format via the client socket in a loop, with a 2-second interval between transmissions.

Server (Receiver)

• Receiving Vital Signs: Receives vital signs data from clients and stores it in a Redis database.
  • Ensure HOST_IP = "Ahmed" is set to your PC's localhost.
  • Sets up a server-side socket and binds it to the specified IP address and port.
  • Creates and connects to an online Redis database, storing vital signs under unique keys.
• Handling Clients: handle_client(client): Receives JSON-formatted data from clients, decodes it, and stores vital signs in Redis.
• Main Server Loop: Listens for incoming connections, accepting and handling clients using the handle_client function.

Qt Creator GUI

• Live Plotting Graph: Displays live graphs of vital signs data using Matplotlib embedded in a Qt application.
  • LivePlotWidget class inherits from FigureCanvas for live plotting.
  • Initializes plots for heart rate and blood pressure, fetching data from Redis.
  • User interface managed by Qt, allowing selection of vital sign type (heart rate or blood pressure) and patient ID for dynamic plotting.
  • Supports real-time updates based on Redis data fetches.

User Interface

• Usage Instructions: Steps on effectively using the patient monitor Qt application:
  • Insert correct patient ID.
  • Select vital sign (heart rate or blood pressure) from the combo box.
  • Press submit to display the live graph.
  • Alternate between vital signs using the combo box.
  • Change patient ID to view another patient’s vital signs.

Dependencies

• Python 3.x
• Qt Creator
• Matplotlib
• Redis
• Other necessary Python libraries

Setup Instructions

1. Set up Redis database and configure connection details in the code.
2. Run server.py to start the server.
3. Run client.py to start sending vital signs data.
4. Launch Qt application (python main.py) to visualize live patient vital signs.

More details are in the pdf

Assignment_4_Video.mp4