Module 1: Introduction to GUI Development

Topics Covered:

• Overview of Python for GUI development.
• Introduction to PyQt and its features.
• Setting up the development environment.

Project:

• Create a basic PyQt window with buttons and labels.

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Module 2: Serial Communication with Arduino

Topics Covered:

• Understanding serial communication.
• Setting up Arduino for data transmission.
• Receiving and displaying data in Python.

Project:

• Build a simple Python GUI to read data from an Arduino sensor (e.g., temperature or light).

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Module 3: Real-Time Data Visualization

Topics Covered:

• Using PyQtGraph for plotting real-time data.
• Customizing graph appearance (axes, labels, colors).
• Updating plots dynamically with sensor data.

Project:

• Develop a GUI that plots real-time data from an ultrasonic sensor.

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Module 4: Motor Control via GUI

Topics Covered:

• Basics of controlling DC and Servo motors with Arduino.
• Sending commands from Python to Arduino.
• GUI buttons and sliders for motor control.

Projects:

1. Create a GUI to control DC motor speed and direction.
2. Build a GUI with a slider to adjust Servo motor angle.

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Module 5: Storing Data in CSV Files

Topics Covered:

• Writing data to CSV files using Python.
• Formatting and organizing data for analysis.
• Saving sensor readings from the GUI.

Project:

• Develop a GUI that stores temperature and light sensor data in a CSV file.

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Module 6: Advanced GUI Features with OpenGL

Topics Covered:

• Introduction to OpenGL for 3D graphics.
• Rendering real-time 3D visualizations of sensor data.
• Combining OpenGL with PyQt for advanced interfaces.
• Visualizing IMU data (orientation and motion) in 3D.

Project:

• Create a 3D model in OpenGL that moves based on IMU sensor input (e.g., pitch, roll, and yaw).

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Module 7: Final Project – Integrated Control and Monitoring System

Project:

• Develop a comprehensive GUI that:
  • Acquires and displays real-time data from multiple sensors.
  • Visualizes IMU data dynamically in 3D using OpenGL.
  • Controls DC and Servo motors interactively.
  • Plots data in real-time and saves it to a CSV file.
  • Includes 3D visualization for dynamic sensor readings.

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Learning Outcomes:

• Design and develop intuitive GUIs using PyQt.
• Integrate Python with Arduino for seamless data communication.
• Create real-time data visualizations and motor control interfaces.
• Visualize IMU data in 3D using OpenGL.
• Store and manage sensor data efficiently in CSV format.
• Utilize OpenGL for advanced 3D visualizations.

This course is ideal for students, hobbyists, and engineers looking to enhance their skills in software-hardware integration and GUI development for robotics and IoT systems.