The Wait is Over: LTS Java 25 brings FFM to #JavaOnRaspberryPi

Since 2012, Pi4J has enabled Java to control electronic components connected to the Raspberry Pi's GPIO pins. However, both Java and the Raspberry Pi have evolved significantly since then. Supporting new hardware has been a challenge, requiring multiple implementations in the Pi4J library with a significant amount of complex code based on the Java Native Interface (JNI) and Java Native Access (JNA).

The Foreign Function & Memory (FFM) API, finalized in Java 22, promised to make such integrations with native code a lot easier. With Java reaching a new Long Term Support version, the Pi4J project bumped to Java 25 and makes full use of FFM!

In this talk, you’ll learn how this FFM implementation is much easier to support and achieves high performance due to less memory copying and less interop code. It will also help improve the Pi4J project by reducing dependencies, minimizing the JAR footprint, supporting additional protocols, and enhancing compatibility with more SoCs.

Through live demos, you will learn how to control LEDs, read buttons, interface with LCD displays, and gather sensor data. You'll see how FFM makes hardware interaction as natural as regular Java programming, and you will be ready to start your own experiments as soon as you arrive home.

Target audience: Java developers interested in IoT, embedded systems, and hardware programming. Basic Java knowledge is required, but no prior experience with Pi4J or electronics is needed.

Building Smart Devices using Java on the RaspberryPi - An intro to Pi4J.

A Raspberry Pi is a full Linux PC with a small form factor and a low price of between 6 and 95€. And of course, you can run Java on it. The same kind of JVM applications you know, love, and use on heavy machines can also be used on the Raspberry Pi. "Write once, run everywhere"? Ah yes, that's the promise of Java! But this small board has some additional possibilities you will not find on that fancy server you are running somewhere in the cloud.

Do you need a touch-screen device to interact with your home automation or a machine? JavaFX, the new Raspberry Pi Zero 2 W (15€), and a touchscreen are the perfect and affordable combo to provide the perfect solution. Yes, with its low price but high specifications, Raspberry Pi is opening whole new worlds.

And on top of that, all Raspberry Pis have those 40 magical pins to connect an unlimited choice of electronic components. Measuring temperatures and distances, toggling LEDs and relays, controlling the content on a LED matrix or LCD display, playing the Star Wars tune on a buzzer,... the only limit is your imagination! In this talk, we'll take a look at the current state of Pi4J (www.pi4j.com) and dive into the code of a few of these example use-cases. Let's experiment with Java on a CrowPi - a Raspberry Pi-based laptop - to read values from sensors and control other electronic components, and show the values on a JavaFX dashboard.

Java is not only the server language running on heavy machines! You can do amazing stuff with it on a 15€ computer and gain new knowledge at the same time, like controlling electronic components and different communication protocols.

What I Learned About OpenJDK as a Docs Writer

As a teenager, a Commodore 64 and DIY solder kits ignited my passion for computers and electronics. But for some obscure reason, I chose an unexpected path by attending film school. I graduated when video and television moved from analog to digital, and the first connected computers began shaping the foundation of the internet we know today. My journey eventually led me to web and software development, where I discovered Java nearly 15 years ago. Since then, Java has been my primary programming language.

In the summer of 2022, my life took an exciting turn when I joined Azul as a technical writer. Suddenly, I found myself surrounded by people who had been working on Java since the early start and even contributed to some of the core libraries. A whole new world opened for me! I learned more about the OpenJDK project's internals than I ever imagined when I was using Java as a developer...

How many Garbage Collectors do you know in Java? Did you know your Java program needs a warm-up time? Are you familiar with the various stages of the JIT compiler? The ongoing debate between JIT and AOT compilation? And how tools like CRaC, ReadyNow, and Falcon can help you to run your code faster?

Let me take you on a journey through OpenJDK-land, and what I learned about how Java starts an application, compiles the code, and needs time to reach its maximum performance. This expedition will also give you an insight into how the OpenJDK project is organized and what information you can find in its sources.

Brace yourself for some exciting findings because, as it turns out, experimenting with Java on the Raspberry Pi also taught me new things about optimizing Java application performance!

Looking at Music, Again. What a Dad, a Pianist Son, and AI Built Together

When a nerdy dad and his musician son join forces, some nice things can happen. MelodyMatrix started as a small MIDI experiment and grew into a full project. We presented it in 2024 with a live piano performance at Devoxx and J-Fall to prove it. A year later, AI entered the workflow.

Vik is back at the piano. Frank is back with his laptop. And we bring AI-assisted coding to the stage to demonstrate a workflow that actually worked.

You'll see how AI turned a photo of a hand-drawn chord diagram into a working JavaFX dynamic view, generated a drum set visualization from a description, and how a disciplined `@Architect`/`@Coder` workflow hunted down frame-by-frame rendering differences in Lottie animations. The key insight: design before prompting, keep sessions scoped, and let the failing test tell you what to fix next.

We also used this workflow to improve websites, achieve better SEO results, generate UI views, and burn too many API tokens. You'll see the bill.

No framework benchmarks. No enterprise use cases. Just two people, one piano, a few open-source projects, and an honest look at what systematic AI-assisted coding feels like from the inside.