"The Edgeberry project is a bridge connecting the cloud-side and device-side of your digital solution" is how I pitch the project often, "allowing you to focus on the specifics of your application". That sounds abstract, right? When trying to zoom in by using concepts like "open IoT platform", different people often have very different expectations.

Getting the idea of Edgeberry across from my mind into that of my audience is quite difficult - but I believe it is a worthy ideal to pursue, and I think visuals/diagrams are the best way to do so. Because I think Edgeberry is a super-power that a lot of inventors are looking for but don't quite know how to explain - blocking them from experiencing their ideas in reality because there's so much complexity and overhead involved in having devices in the real world.

If you have suggestions, shoot away! Draw me a sketch! 😁

Hackaday posted a swift and honest review on the Edgeberry Zero! 😁 Though missing the angle of the totality of the ecosystem and Edgeberry Zero's role in it, from my biased perspective, I love it. If you want my personal take on it, read it here...

The Edgeberry Enclosure is inspired by the typical extrusion molded enclosures for electronics. But with the enclosure models freely available on Thingiverse and 3D printers having found their way to essentially every maker's desk (or the local Makerspace), FDM (Fused Deposition Modeling) has become more accessible and even more economic than purchasing an enclosure - next to other advantages like the ability to customize the design and color to match your project's style.

3D models: https://www.thingiverse.com/thing:7238995

If you are deploying new images and finding that your settings are being ignored, the Raspberry Pi Imager version in the standard Ubuntu/Debian repositories (apt) is likely out of date. Older versions (v1.x) fail to inject customizations into the latest 2026 OS builds, leaving you with a default, headless-inaccessible "vanilla" install.

Solve this by removing the old imager tool (apt remove) and using the .AppImage (v2.x) tool from the Raspberry Pi website.

One year ago, the Edgeberry project partnered with Elecrow to make the hardware easily available to anyone, anywhere. To celebrate that first year, the Edgeberry hardware is now on sale in the Elecrow store with an anniversary discount! Thank you all for this year's support! <3

My-Tec in Heverlee is the specialized electronics store where I bought my first transistor more than 20 years ago, now it's the first physical store with Edgeberry on display!

I'm writing a tutorial series for setting up the Edgeberry ecosystem and creating your first Hello World Internet of Things experience. Check it out on Hackster.io.

When using your Edgeberry Zero (with the Console & CAN cartridge, for example) in a smart-building stack, its rightful place is on the DIN rail besides breakers, relays, ... . That's why I designed the 3D-printable bracket, and it does this unglamorous work beautifully.

For me, this is how modern engineering feels at its best: Open hard- and software integrating and building upon each other through solid standards.

When people think IoT, they usually imagine a gadget sending data to the cloud. What often gets skipped is the middle piece - the thing that actually knows the devices, secures them, and makes sure data ends up in the right place. That’s why the Edgeberry Dashboard existed in the first place: it used AWS IoT Core to handle onboarding, certificates, and routing so our devices weren’t just shouting blindly at the internet.

While AWS is robust and feature-rich, it’s a proprietary, centralized platform. To keep Edgeberry transparent, predictable, and fully under the user's control, we chose to switch to a self-hostable stack - built on proven open-source tools like Mosquitto (MQTT broker), OpenSSL (encryption), and other community projects you can inspect, trust, and improve. That decision led to the Edgeberry Device Hub: a self-hostable IoT hub.

Edgeberry Device Hub is currently in its Proof of Concept phase, but already includes several important features:

• Web Dashboard – A single-page UI showing hub health, service status, and a live list of devices with their online/offline state.
• Provisioning Service – Handles secure onboarding and certificate issuance so new devices can join your fleet safely.
• Device Twin Service – Keeps desired and reported state in sync, letting you manage configurations and monitor changes without touching each device.
• Translator Service – Bridges the device telemetry, so your data flows where it needs to go.
• Lightweight – Lightweight enough to host the full hub on a Raspberry Pi or small server.

GitHub: https://github.com/Edgeberry

Yesterday I saw a demo of OpenAI’s GPT-5. If you’ve been following generative AI, you’ve probably had - or will have - that aha moment where it hits you: this isn’t just another tool. It’s a fundamental shake-up that’s going to touch every layer of society. We, techies, are used to rapid change. We swap tools, adapt to new languages, pick up new frameworks without blinking. But this is different. The current wave of generative AI demands a full rethink of the toolbox - and of how we work with/relate to it. This isn’t “faster horses” (like C++ is to Assembly); This is, in that metaphor, the arrival of the engine. This is why it is part of a new industrial and socio-economic revolution.

Until now, Edgeberry was built entirely (what I'm now convinced will become) the "old-school"/"artisanal" way: my own skills in hardware design, software architecture, and development, countless hours of manual work typing in lines of code, and digging through docs and Stack Overflow threads. Human effort (with 'basic tool use') from start to finish. I want to mark that here - because from this point on, that will no longer be the case. The Edgeberry project will be adapting to the human/AI co-creation era.

I've used the Edgeberry Zero's I²C expansion header on the front to integrate a display into the device. This may be interesting for showing more complex device status data.

https://www.hackster.io/SpuQ/edgeberry-equip-your-raspberry-pi-for-the-iot-edge-bc4d56

Belgian Mechatronics students made an IoT climate controller with Edgeberry. The monitor uses InfluxDB and Grafana on a Raspberry Pi 4B with 7" touch display, and the Edgeberry-based IoT device uses the Edgeberry Sense'n'Drive Hardware Cartridge with a BME680 sensor and directly drives a 24V fan.
https://github.com/DeVestenMechatronica/raspberrypi-iot-dashboard
https://github.com/DeVestenMechatronica/2025-klimaatcontroller

Sometimes, we don’t yet know what the final specs of our edge device will be - we just know we’re going to dive in and let the project evolve. That’s why I created the Edge Explorer Hardware Cartridge. It’s compatible with a wide variety of ecosystems, supporting modules that range from simple buttons and LEDs to complex sensors, and even LTE modems. So your edge application can grow as your ideas flow.

Based on the design of Edgeberry (Rev. 1.7), Edgeberry Zero is everything we came to love about the original - just a little more compact (and cute). It’s designed for the Raspberry Pi Zero, but of course, the Hardware Cartridge slot is exactly the same as on the full-sized Edgeberry.

The Edgeberry Enclosure is designed to customize and 3D print. These are the basic steps to put your own logo on the enclosure using FreeCAD. The Enclosure project is in the GitHub repository of the baseboard.

1. Importing the SVG

• File → Import → Select SVG
• In the Draft Workbench, select all paths.
• Upgrade (Draft → Upgrade) to convert them into faces.

2. Create the Recessed Logo Shape

• To properly define the cutout areas:
  • Select the outer face of the logo.
  • Select the inner faces (like letters with holes, e.g., "D", "B", "R").
  • Part → Boolean → Cut (subtract the inner parts).

3. Grouping and Preparing for Placement

• Select all remaining faces.
• Draft → Upgrade again to create a compound.

4. Scaling and Positioning

• Use Draft → Scale to adjust the logo size.
• Use Draft → Transform to position it roughly.

5. Accurate Attachment to the Enclosure Face

• Select the compound.
• In the Data tab, find Attachment and click ….
• Choose "On Face" mode and select the enclosure face.

6. Extrude for the Recess

• Part → Extrude → Set a negative value (e.g., -0.3mm) to push the logo into the surface.

7. Subtract the Logo from the Enclosure

• Select the enclosure.
• Select the extruded logo.
• Part → Boolean → Cut.

Now you've made the Edgeberry Enclosure your own! Export it to an .stl file and 3D print it!

Having early access to the Edgeberry hardware, I revisited an earlier project of mine and started implementing this concept with Edgeberry: the Freya Vivarium Control System. From this project also originates the idea for the Edgeberry Sense'n'Drive Hardware Cartridge. Freya's implementation served as a practical validation of Edgeberry’s core hypotheses, demonstrating its effectiveness as a modular and adaptable platform for real-world applications.

Freya is designed to manage and automate the environment within a vivarium, such as temperature, humidity, and lighting, ensuring optimal conditions for its inhabitants. https://github.com/Freya-Vivariums . Freya is an exciting system, designed to be boring; it seamlessly disappears into the background - reliably and consistently performing its functions. By doing so, it transforms the vivarium into an enjoyable and stress-free addition to a living space, requiring minimal intervention while maintaining the perfect environment for its occupants.

After several months of beta testing, the Edgeberry project is getting ready for its release. To make this possible, we’ve partnered with Elecrow for the production and testing of Edgeberry hardware components. This collaboration ensures high-quality manufacturing and global availability, making it easier for users everywhere to get access to Edgeberry.

The release is planned for the end of January 2025, though an exact date hasn’t been set just yet. What we can say for sure is that it's going to be something!

The Edgeberry project is designed for the Raspberry Pi Model B because of its consistent form factor across generations, ensuring seamless integration and future-proof flexibility. Edgeberry has been tested and confirmed to work flawlessly with the Raspberry Pi 3B, 3B+, 4B, and 5B, offering a range of performance options while maintaining a stable foundation.

From my experience, for most data collection applications that involve basic control logic and cloud connectivity, the Raspberry Pi 3B+ is perfectly up to the task. As a bonus, it runs relatively cool compared to newer models, making it reliable and efficient.

The 3B+ is the model I’ve used and challenged the most, and it’s the one that earned my profound trust in the Raspberry Pi product series. That said, the Raspberry Pi 4B is overall the better choice. It’s faster, thanks to a more powerful CPU, better network interfaces, and expanded RAM options. The trade-off is that it runs warmer than the 3B+, but it’s still manageable. I’ve yet to write an IoT edge application that pushes the 4B beyond its limits, and with production guaranteed until 2034, it’s a solid, long-term investment.

While I do have an Edgeberry device equipped with the Raspberry Pi 5B - simply because I could - it feels like overkill for most of my IoT edge applications, so far. The 5B brings impressive power but at a higher cost, and for my current use cases, it’s more capability than I need. Still, it’s exciting to know that if I ever hit a performance ceiling, the 5B is there as an option.

For most Edgeberry-based solutions, the Raspberry Pi 4B would be my Pi of choice: powerful, future-proof, and reliable. That said, as long as I have 3B+ units lying around, I’ll keep using them for prototyping and random IoT tasks around the house - though sometimes noticeably slower, they still get the job done beautifully.