Description
Course Structure
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.
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).
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.
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:
- Create a GUI to control DC motor speed and direction.
- Build a GUI with a slider to adjust Servo motor angle.
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.
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).
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.
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.





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