For many participants, this was their first time using QNX, and the experience became a week of learning, troubleshooting, building, and turning new ideas into working prototypes, while also balancing midterms at the same time.

The three winning teams each approached the QNX track differently, but they shared a common mindset: a willingness to try something new. Whether they were drawn in by the hardware, the challenge of learning a new RTOS, or simply the opportunity to build something different, each team used the experience to stretch their skills and explore what was possible with QNX on Raspberry Pi.

First Place: Team April

Caitlyn Fong, Myles Harris

Caitlyn and Myles combined their backgrounds in electrical and computer engineering, artificial intelligence, and computer vision to build a robot car that could navigate using a phone camera feed and AprilTags placed around the robot. Rather than relying on a camera mounted directly on the device, their system used visual cues from the user’s perspective to determine the robot’s orientation and movement.

Along the way, they worked through motor-control issues, signal challenges, and software compatibility hurdles, all while learning a new platform for the first time. They described the QNX setup process as clear and approachable, and highlighted documentation and support resources as helpful throughout the week.

Their project reflected exactly what experimentation should look like: combining different skill sets, solving problems in real time, and refining an idea through testing. By the end of the challenge, they had not only built a working system but also gained a new perspective on embedded development. As Caitlyn reflected, “It made me realize that Raspberry Pis are definitely microcontrollers I can look into for systems like this in the future.”

Second Place: Pied Pipers

Sascha Kudrytski, Hyeyoon Song, Elisha Rahardja, Sabrina Yang

For the Pied Pipers, the QNX track began as a pivot. After originally planning to join the general track, the team ended up in QNX and decided to make the most of the opportunity. That quick change of plans led to a creative, multidisciplinary project that blended hardware, software, and a musical theme.

Using the components available in their kit, the team built a music-focused project based on light sensors and an analog-to-digital converter, where covering a sensor would trigger a corresponding note. They had originally hoped to add a 3D-printed mechanical finger to physically interact with the sensors, but time and printing issues meant they had to simplify the final design.

Even with those constraints, the team embraced the learning process. They encountered networking and interface challenges, worked through them with QNX support, and came away with a strong sense of how refreshing it can be to build in a new environment. For team members interested in robotics and embedded systems, the track offered valuable exposure to the software side of engineering.

Third Place: Team Vibrado

Isaac Osei, Wasmir Chowdhury

Team Vibrado focused on a project with clear real-world relevance: a vibration-monitoring system built with an accelerometer and Raspberry Pi running QNX. Their prototype established a baseline vibration frequency for a machine, then detected deviations that could indicate a mechanical issue. The concept was inspired in part by coursework in dynamic systems and by the team’s interest in building something that aligned with QNX’s real-time capabilities.

What makes their result especially impressive is the timeline. Due to exams and assignments, the team only had about two days of focused build time, yet still delivered a thoughtful project that connected classroom concepts to a practical industrial use case.

They also found value in the tools already available within the QNX environment, particularly the local libraries that helped them move quickly without needing to build everything from scratch. For them, the challenge was not just about making something work — it was about designing something relevant, useful, and grounded in how QNX is used in the real world.

Learning by Building

One of the clearest takeaways from these conversations is that students do not need prior experience with QNX to start building with it. In fact, for these teams, much of the value came from learning as they went — exploring unfamiliar tools, adapting to setbacks, and turning initial experimentation into something concrete.

That spirit of experimentation is exactly what QNX Everywhere is designed to support. When students have the opportunity to work hands-on with real technology, they gain more than technical exposure. They build confidence, problem-solving skills, and a better understanding of how embedded systems come to life in practical applications.

Ready to start building yourself?

QNX Everywhere makes it possible for anyone to experiment with QNX for free, with a free non-commercial QNX SDP 8.0 license and quick-start paths for Raspberry Pi and QEMU. Join our growing developer community on Discord to meet fellow QNX engineers, ask questions, or collaborate on a new project.