EmbeddedOnLinuxLR

Learning route for my Embedded Systems on Linux course (UNAL 2025-2)

Course taught by Prof. Juan Bernardo Gomez Mendoza – Universidad Nacional de Colombia, Sede Manizales

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Course Overview

This repository documents the complete learning route for the course Programación de Sistemas Linux Embebidos (Embedded Linux Programming 4201152).
Students explore embedded systems development through Linux, from kernel space to user space, combining C, Python, and shell scripting.

Course Goals

• Understand embedded Linux architecture and low-power SoC platforms.
• Develop simple user- and kernel-space applications.
• Work with drivers, APIs, and system-level software.
• Integrate machine–machine (M2M) and human–machine (HMI) interfaces.

Methodology

• Combination of lectures + hands-on labs.
• Use of virtual machines, WSL, Docker, and SBCs (Raspberry Pi 3/4, BeaglePlay, Lichee RV, etc. (rapspberry pi used on this case)).
• Tasks include writing C programs, shell scripts, kernel modules, and Python utilities.

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Branch Strategy

To keep the work organized, this repo uses a branching model:

• main
  Main branch. Contains stable, reviewed, and clean code/documentation.
  Always reflects the state of the project that is ready to be delivered or referenced.

• dev
  Development branch. Contains ongoing work and integrates features before merging into main.
  All new features or experiments should be branched off dev.

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Repository Structure

EmbeddedOnLinuxLR/
├── content/
├── work/
│   ├── work/
│   ├── code/
├── project/
│       ├── Include/ | Lib/ | nbs/ | Scripts/
└── README.md

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Practical Workflow

sudo apt install build-essential git libncurses5-dev
make
./cpuInfo
python3 -m venv work/embeddedOnLinuxPYDevEnv
source work/embeddedOnLinuxPYDevEnv/bin/activate

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Key Concepts Summary

• Linux services = daemons managed by systemd.
• /proc = virtual filesystem for kernel info.
• Embedded Linux = multi-layered abstraction system.
• Debugging tools: valgrind, ddd, kcachegrind.
• ncurses enables TUI interaction for resource monitoring.

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Notes and Resources

all course contente inside content dir

• Class notes → content/lectures/
• Presentations → content/classContent/
• interest papers → /papers/
• code and courses from class → code
• work and projects → work space

work in progress inside dev Env dir

• work progress and deliverys → workspace/

• simulations → simulations/

• environments → local development environment/

• Reference →

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Roadmap

• Repository structure and environment setup
• Import lecture notes and materials
• task as : -rial time monitor resource -Kernel module exercise (heartbeat service) -Raspberry Pi deployment, conection and SSH access -Call-graph visualization in Python and C -services implementation -modular and polymorphism implementation
• project advances
• project delivery

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Author

Mateo Almeida (Macreat)
Course: Embedded Systems on Linux @ UNAL 2025-2
GitHub: @Macreat

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License

x
For academic and learning purposes only.