LuckFox Microcontroller Laboratory

Introduction to LuckFox for Embedded Systems and IoT Applications

Welcome to the LuckFox Mini-course, where we will explore the fundamentals of embedded systems, networking, and IoT applications using the LuckFox Pro/Max development board. This Mini-course will guide you through setting up your LuckFox, configuring its environment, and leveraging its capabilities to build networked applications and sensor-based projects.

What is the LuckFox?

The LuckFox Pro/Max is a compact ARM-based embedded computing platform designed for developers, engineers, and students working with Linux-based single-board computers (SBCs). It provides an excellent low-power computing environment with network connectivity, GPIO control, and Python programming support—making it ideal for IoT (Internet of Things) and automation projects.

By working with the LuckFox, you will gain hands-on experience with Linux, embedded systems programming, and cloud-based data logging—all essential skills for modern engineering and applied physics.

Mini-Course Overview

This course will walk you through the step-by-step setup and development of applications using the LuckFox Pro/Max. By the end, you will have a working IoT-capable system that interacts with web servers, cloud services, and physical hardware.

🔹 Course Topics

By completing these topics, you will develop an understanding of how embedded systems integrate with cloud services and networked applications, preparing you for more advanced IoT and automation projects.

Materials and Supplies

Fortunately the LuckFox Pico Pro/Max is inexpensive and readily available. While you could get a good deal out of this mini-course with just a LuckFox Pro or LuckFox Max, you would get additional benefit by having a breadboard and some basic electronics. In the videos, we are using a LuckFox Pico Max from Waveshare.

The LuckFox Pico Pro/Max Tutorial page from LuckFox is available here.

Setting up Ubunutu on the LuckFox by Fusion Automate.

The setup guide is available here

The video playlist is available here.

Text Files:

plot_test.txt

flaskapp.txt

  GoogleSheets.txt

  Blink.txt

  GPIOin.txt