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Zephyr RTOS is a lightweight and flexible real-time operating system tailored for embedded systems and devices with limited resources, like microcontrollers. Developed as a collaborative project hosted by the Linux Foundation, Zephyr supports multiple architectures and is released under the Apache License 2.0.

Zephyr is commonly used in IoT applications and other embedded systems where efficiency and reliability are essential.

Website - https://www.zephyrproject.org/

Git - https://github.com/zephyrproject-rtos/zephyr/

Documentation - https://docs.zephyrproject.org/latest/index.html

Discord - https://discord.com/invite/Ck7jw53nU2

Getting Started Guide - https://docs.zephyrproject.org/latest/develop/getting_started/index.html

Code Licenses - Apache 2.0

Machine-Learning-related project

1 contributor medium-size (175 hours)

Level of difficulty: Intermediate

Zephyr is an open-source, real-time operating system (RTOS) optimized for resource-constrained devices, making it ideal for IoT and embedded systems. It supports multiple architectures and has a modular design.

For machine learning (ML) with Zephyr, developers can integrate frameworks like TensorFlow Lite for Microcontrollers (TFLM) or Edge Impulse. These allow small, efficient ML models to run on devices with limited CPU and memory resources.

The i.MX series from NXP features powerful DSP cores that can offload computational workloads from the main CPU.

This project will focus on leveraging Zephyr RTOS to manage ML workloads on these DSPs efficiently. It will require porting or optimizing existing ML frameworks for the DSP, designing APIs for seamless integration, and demonstrating an end-to-end ML pipeline running on Zephyr. Potential deliverables include support for TFLM on the DSP, and a sample application showcasing the implementation.

Expected Outcomes:

• Integration of ML inference frameworks (such as TFLM) on NXP DSPs running Zephyr
• Sample applications demonstrating ML inference (e.g., speech recognition, anomaly detection)
• Documentation and tutorials for deploying ML workloads on NXP DSPs
• Submit pull requests to Zephyr’s upstream repository

Skills Required:

• C/C++ programming
• Embedded systems and real-time operating systems (Zephyr)
• Familiarity with TensorFlow Lite Micro or similar lightweight ML frameworks
• Familiarity with version control systems (e.g., Git)

Mentors:

• Iuliana Prodan iuliana.prodan@nxp.com
• George Stefan george.stefan@nxp.com
• Daniel Baluta daniel.baluta@gmail.com
• Laurentiu Mihalcea laurentiu.mihalcea@nxp.com

1 contributor full-size (350 hours)

Level of difficulty: Intermediate

Probably many of you have already thought about that one can take an SBC, install Linux and CUPS or a Printer Application on it, and connect this to an old printer which is still mechanically perfect but needs a driver which is not available any more for some operating systems. Suddenly the printer turns into a modern, driverless IPP printer which can be used with any operating system.

But it is a little awkward having a little box dangling behind the printer which also occupies a power outlet. Also one can perhaps also make use of much cheaper SBC.

Imagine you could buy a tiny board for a few dollars and put it somewhere inside the printer and grab its power from the printer's power supply.

Such tiny boards are often not powerful enough to run Linux, but there is also the much more lightweight Zephyr operating system. This is a system for IoT applications on low-footprint hardware.

And this scenario does not only serve for cheap DIY solutions to save old printers, it also can be a base for cost-effective printer firmware development.

This project is about investigating whether one could run the components of the free software printing stack, as CUPS, PAPPL, libcupsfilters, … under the Zephyr operating system, and actually let this tiny print server execute printer drivers and print on legacy printers. Also the handling of print data and the need of resources here needs to be investigated. Can we hold several pages? Can we use Ghostscript? Or do we have to stream raster print data from the client to the printer?

Most desirable is to do this with PAPPL (Printer APPlication Library), as it is designed to emulate a driverless IPP printer in software, including the so-called “Gadget” mode to appear as an IPP-over-USB device when connecting the power supply USB port of the SBC with the client computer's USB.

Code License: Apache 2.0, MIT (licenses of the OpenPrinting projects)

Skills Required:

• C/C++ programming
• Embedded systems and real-time operating systems (Zephyr)
• Familiarity with version control systems (e.g., Git)

Mentors:

• Till Kamppeter till@linux.com (Project lead OpenPrinting)
• Iuliana Prodan iuliana.prodan@nxp.com
• Zephyr Developers TBD