Raspberry Pi 5

27 Articles

Poking At The Radxa Dragon Q8B Raspberry Pi 5 Killer

October 10, 2026 by 23 Comments

Although the asking price of $209 plus shipping seems high for the Radxa Dragon Q8B, featuring the Qualcomm SC8280XP and 8 GB of LPDDR4X, this is 2026, and amid the RAMpocalypse, even the 8 GB LPDDR4X-equipped Raspberry Pi 5 now costs $175. This, to [Jeff Geerling], makes it fair to directly compare the two to see whether you may want to consider this board for more intense computing purposes.

There’s also a written summary of the results and details in a GitHub issue, though the direct comparison with the Raspberry Pi 5 is in the video.

Although this Qualcomm SoC isn’t new, its primary use is for Windows laptops, which gives somewhat of a hint as to what its performance may be like, tempered by the fact that it was announced in 2021.

The Dragon QXB offers about 2x everything over the RPi5, plus Windows and UEFI support. For Linux, it appears that you still need customized images, which seems perplexing in light of the UEFI aspect. You also have to pick between different Linux images from Radxa and use their Rsetup update tool, making it a less than newbie-friendly offering.

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Solar Powered Traffic Monitoring

September 24, 2026 by 8 Comments

[Marios Christoforou] recently undertook a Computer Engineering degree at the University of Cyprus. His final year project involved implementing a solar-powered device to count vehicular traffic, while logging results to the cloud.

The project is built around a Raspberry Pi 5, specifically the version with 4 GB of RAM. It runs Raspberry Pi OS and is equipped with a basic webcam with 720p video output. The single-board computer runs off a 12 volt lead acid battery, which is charged via a 100 W solar panel hooked up to a basic charger module. Identifying vehicles in traffic is achieved with the YOLOv8 Nano machine vision model, which outputs bounding boxes around cars, trucks, buses, and motorcycles captured in the webcam feed. Software algorithms are used to ensure vehicles are only counted once as they pass through the camera’s field of view.

There’s plenty of detail on how the project was refined to meet initial goals. To make the most of the solar power available, [Marios] optimized the setup with an eye to performance and low power draw. To that end, the Raspberry Pi had Bluetooth, the PCIe slot, audio, and HDMI ports all disabled, while the CPU and GPU were both under-clocked for good measure. Software tweaks were also used, like running headless and dropping unimportant parts of the video frame for more efficiency.

We’ve featured other homebrew traffic monitors before. These days, though, it’s Flock cameras that seem to be making all the headlines in this area.

Pi 5 Becomes ALSA-Compatible TOSLINK Sound Card

July 8, 2026 by 11 Comments

This is one of those hacks that makes you stop in your tracks and say, “wait, you can do that!?” — before realizing, oh, yes, of course you can do that. With enough computational power, you can do a lot of things, and the Raspberry Pi 5 is a far cry from the single-board computer’s humble beginnings. In this case, the “you can do that!?” is both that [Oliver] was able to get the digital audio TOSLINK working via an LED tied to one GPIO pin on the Pi, but also the larger project that is embedded in: using the Pi as a full featured 8-channel USB sound card called Camilla DSP.

For the first one: the old TOSLink standard is very simple, and all you need to do is blink an LED quickly enough. Considering the clock frequency of the Pi 5 is in the GHz range and the TOSLINK is the same 3.1 Mbit/s S/PDIF signal you could pull off your CD-ROM drive to your Sound Blaster, there’s no problem there. Except, wouldn’t the operating system get in the way? Well, not when you have enough clock cycles to throw at the problem. Using a Pi 5 doesn’t hurt: the RP1 I/O chip included on the board is keeping things smooth with its included PIO while Linux mucks about in the background. There’s a reason we called it the most important product Raspberry Pi ever made.

As for making a USB sound card from an SBC — well, we’re not sure why that got the “you can do that” reaction. The Raspberry Pi family had ‘gadget mode’ for over a decade now, allowing you to present the computer as a USB device, so why not a sound card? That’s a valid class of USB device.

Make Your Ceiling Disappear With ADS-B And Short-Throw Projector

June 4, 2026 by 15 Comments

If you’re into airplanes, you’ve probably had the experience of hearing an unusual aircraft and rushing outside to try and catch a glimpse of it, all while fumbling with a smartphone to open a flight-tracking app. If your home was equipped with [cpaczek]’s Skylight project, which combines ADS-B data with a short throw projector, that little dance would have been totally unnecessary.

ADS-B or the “Automatic Dependent Surveillance-Broadcast”, is the standard by which aircraft broadcast their position and other flight information from onboard transponders. In most of the world, every commercial aircraft has an ADS-B transmitter, and they’re slowly creeping into general aviation as well. The signals aren’t hard to pick up with software-defined radio — like perhaps this RP2040 based unit we featured — or the RTL-SDR v4 this project calls for.

Using data from ADS-B, the Skylight software runs on Raspberry Pi 5 and renders icons of the aircraft exactly where they would appear above you, if that pesky ceiling wasn’t in the way. You get the flight’s code, destination and flightplan with a nice icon representing what type of airplane it is. Thanks to specifying a Pi 5, the projection is a smooth 60 FPS at 1080p. Airplanes aren’t the only things plotted, though — this is also a planetarium, giving you a full view of the stars and any satellites passing overhead. That’s obviously via an API, not SDR, and if you like you can configure it to track aircraft that way to — allowing you to set your Skylight for anywhere in the world, if you aren’t near an interesting airport.

ADS-B isn’t just for pilots and plane nerds — if you’re flying drones, you probably should keep an eye on it, too. In that case, though, you probably won’t be looking at your ceiling.

Thanks to [Thinkerer] for the tip!

Quote Printer Keeps Receipts

January 3, 2026 by 10 Comments

In the world of social media, “keeping receipts” refers to the practice of storing evidence that may come in handy for a callout post at a later date. For [Teddy Warner], though, it’s more applicable to a little printer he whipped up to record the very best banter from his cadre of friends.

[Teddy’s] idea was simple. He hoped to capture amusing or interesting quotes his friends made in his apartment, and store them in a more permanent form. He also wanted to allow his friends to do the same. To that end, he whipped up a small locally-hosted web interface which his friends could use to record quotes, along with proper attribution. Hosted on a Raspberry Pi 5, the web interface can then truck those quotes out to an 80 mm thermal receipt printer. The anecdote, epithet, or witticism is then spat out with a timestamp in a format roughly approximating a receipt you might get from your local gas station. What’s neat is that [Teddy] was also able to install the entire system within the housing of the Miemieyo receipt printer, by 3D printing a custom base that could house the Pi and a suitable power supply.

Beyond being fun, this system also serves a critical purpose. It creates a paper trail, such that in-jokes, rumors, and insults alike can be traced back to their originating source. No more can Crazy Terry claim to have invented “the Malaga bit,” because the server and the receipt clearly log that Gerald dropped it first at the Boxing Day do.

We’ve seen similar projects before, too. There’s just something neat about holding a bit of paper in your hand.

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Medium Format, 3 GigaPixel Camera Puts It All On The Line (Sensor)

November 7, 2025 by 18 Comments

It’s a bit of a truism that bigger sensors lead to better pictures when it comes to photography. Of course everyone who isn’t a photographer knows that moar megapixles is moar better. So, when [Gigawipf], aka [Yannick Richter] wanted to make a camera, he knew he had to go big or go home. So big he went: a medium format camera with a whopping 3.2 gigapixel resolution.

Now, getting a hold of a sensor like that is not easy, and [Yannick] didn’t even try. The hack starts by tearing down a couple of recent-model Kodak scanners from eBay to get at those sweet CCD line sensors. Yes, this is that classic hack: the scanner camera. Then it’s off to the oscilloscope and the datasheet for some serious reverse-engineering to figure out how to talk to these things. Protocol analysis starts about 4 minutes in of the embedded video, and is worth watching even if you have no interest in photography.

As for what the line sensor will be talking to, why, it’s nothing other than a Rasberry Pi 5, interfacing through a custom PCB that also holds the stepper driver. Remember this is a line sensor camera: the sensor needs to be scanned across the image plane inside the camera, line by line, just as it is in the scanner. He’s using off-the-shelf linear rails to do that job. Technically we suppose you could use a mirror to optically scan the image across a fixed sensor, but scanner cameras have traditionally done it this way and [Yannick] is keeping with tradition. Why not? It works.

Since these images are going to be huge an SD card in the Pi doesn’t cut it, so this is perhaps the only camera out there with an NVMe SSD. The raw data would be 19 GB per image, and though he’s post-processing on the fly to PNG they’re still big pictures.  There probably aren’t too many cameras sporting 8″ touchscreens out there, either, but since the back of the thing is so large, why not? There’s still a CSI camera inside, too, but in this case it’s being used as a digital viewfinder. (Most of us would have made that the camera.) The scanner cam is, of course, far too slow to generate its own previews. The preview camera actually goes onto the same 3D-printed mount as the line sensor, putting it onto the same focal plane as the sensor. Yes, the real-time previews are used to focus the camera.

In many ways, this is the nicest scanner camera we’ve ever featured, but that’s perhaps to be expected: there have been a lot of innovations to facilitate this build since scanner cams were common. Even the 3D printed and aluminum case is professional looking. Of course a big sensor needs a big lens, and after deciding projector lenses weren’t going to cut it, [Yannick] sprung for Pentax 6×7 system lenses, which are made for medium format cameras like this one. Well, not exactly like this one– these lenses were first made for film cameras in the 60s. Still, they offer a huge image, high-quality optics, and manual focus and aperture controls in a format that was easy to 3D-print a mount for.

Is it the most practical camera? Maybe not. Is it an impressive hack? Yes. We’ve always had a soft-spot for scanner cameras, and a in a recent double-ccd camera hack, we were lamenting in the comments that nobody was doing it anymore. So we’re very grateful to [Manawyrm] for sending in the tip.

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Moondream title with man's face visible in background.

Using Moondream AI To Make Your Pi “See” Like A Human

September 23, 2025 by 9 Comments

[Jaryd] from Core Electronics shows us human-like computer vision with Moondream on the Pi 5.

Using the Moondream visual language model, which runs directly on your Raspberry Pi, and not in the cloud, you can answer questions such as “are the clothes on the line?”, “is there a package on the porch?”, “did I leave the fridge open?”, or “is the dog on the bed?” [Jaryd] compares Moondream to an alternative visual AI system, You Only Look Once (YOLO).

Processing a question with Moondream on your Pi can take anywhere from just a few moments to 90 seconds, depending on the model used and the nature of the question. Moondream comes in two varieties, based on size, one is two billion parameters and the other five hundred million parameters. The larger model is more capable and more accurate, but it has a longer processing time — the fastest possible response time coming in at about 22 to 25 seconds. The smaller model is faster, about 8 to 10 seconds, but as you might expect its results are not as good. Indeed, [Jaryd] says the answers can be infuriatingly bad.

In the write-up, [Jaryd] runs you through how to use Moonbeam on your Pi 5 and the video (embedded below) shows it in action. Fair warning though, Moondream is quite RAM intensive so you will need at least 8 GB of memory in your Pi if you want to play along.

If you’re interested in machine vision you might also like to check out Machine Vision Automates Trainspotting With Unique Full-Length Portraits.

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