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A USB flash drive is one of those small essentials you reach for from time to time to back up data or transfer files between your Raspberry Pi and substitute computers. For basics like these, it’s tempting to reach for the cheapest thing on Amazon or whatever you find in your local supermarket, but you can easily end up with a device that has sluggish read and write speeds, fragile casing, or – worst of all – far less storage capacity than it claims. Better to go with something you can rely on: introducing the Raspberry Pi Flash Drive, a compact high-capacity USB 3.0 USB‑A device with fast data transfer and an all‑aluminium enclosure. It’s available now at $30 for 128GB, or $55 for 256GB.
We’ve brought our usual exacting standards and attention to detail to our new accessory. It can sustain a write speed of 75MB/s (128GB variant) or 150MB/s (256GB variant), and our thorough testing has made sure it can handle the demands of real life when it comes to sudden disconnection and power failure. Its ergonomic all-aluminium enclosure is easy to grasp and almost impossible to break, although you’ll manage it if, like jdb of this parish, you go at it with a blowtorch. It has an attachment hole so you can keep it on a keyring or similar. The Raspberry Pi logo is etched with classy understatement onto its upper surface.
Fast and robust
Like many high-density NAND flash storage devices, the Raspberry Pi Flash Drive employs a small reservation of pseudo-SLC cache to improve performance under burst-y write workloads. In the background, any writes that were allocated in pSLC are streamed out to the higher-density, but slower, QLC flash. There are significant advantages to doing this: for short periods, the sequential write speed can be almost as fast as USB 3.0 will go.
This cache does, however, make benchmarking challenging. For this reason, the USB 3.0 performance figures we quote are sustained figures, where writes are measured when the cache is forced to do write‑through due to the volume of writes already committed, and reads are measured with the cache empty.
It goes without saying that whatever internal storage arrangement is used, it must be robust against surprise removal or power failure. We verified that our new flash drive meets this requirement over tens of thousands of random power cycles while running intermittently intensive I/O workloads.
Bonus features
In addition to being fast, we made sure that these drives support SSD-style SMART health reporting to help you to manage the device lifespan, as well as supporting TRIM operations. They will also autonomously enter low-power USB 3.0 states when idle.
More handy essentials from Raspberry Pi
Our new flash drive joins a growing range of rigorously specified and robustly tested Raspberry Pi accessories designed to make your day-to-day computing life as friction-free as possible. Raspberry Pi SD Cards and Raspberry Pi SSDs offer you a choice of storage solutions; the four-way Raspberry Pi USB 3 Hub provides an excellent alternative to unsatisfactory price/quality compromises elsewhere; and the Raspberry Pi Bumper is exactly what you need to protect the base and edges of your Raspberry Pi 5, without obstructing access to anything else.
The new Raspberry Pi Flash Drive gives you compact, portable storage with reliable performance for both 128GB and 256GB capacity options. Grab one from a Raspberry Pi Approved Reseller today.
If you’ve ever tried using a Raspberry Pi — or any single-board computer — while travelling, you probably know how frustrating it can be. Hotel rooms with no spare Ethernet ports, conference Wi-Fi behind captive portals, networks that block local discovery tools, or simply not knowing what IP address your headless board received can all turn a simple task into a hassle.
Last year, I came across a concept that sounded like the ideal solution: Ethernet over USB. The idea is beautifully simple — plug the Raspberry Pi into a laptop and it appears as a USB network adapter, just like when you enable USB tethering on a smartphone. That would mean no Wi-Fi setup, no IP scanning, no captive portal headaches — just plug in, SSH, and start working. Bonus: The host computer could even share its internet connection over that same cable.
At least, that’s the theory.
In reality, getting this to work has traditionally involved a mix of outdated scripts, manual configuration steps, and platform-specific instructions that only reliably supported one host OS at a time — Windows, macOS, or Linux, but rarely all three. Many great community efforts exist, but they often require you to clone repositories, edit system files, or manually switch the Raspberry Pi between Internet Connection Sharing (ICS) and normal local networking — and ICS is typically treated as an optional afterthought, rather than part of a unified workflow.
I wanted to streamline that experience — not to replace community solutions, but to offer a clean, all-in-one option that “just works”, regardless of whether the user is a first-time Raspberry Pi owner or someone deploying a fleet of headless boards.
So I started a project with a clear goal in mind: to make a single Debian package that enables USB gadget networking straight out of the box on all supported Raspberry Pi boards, and across all major host operating systems.
Introducing rpi-usb-gadget
Starting with Raspberry Pi OS Trixie images dated 20.10.2025 and later, a new package called rpi-usb-gadget is included by default. It can be enabled with a single toggle in Raspberry Pi Imager, making USB networking setup drastically simpler.
Once enabled:
Your Raspberry Pi will present itself as a USB Ethernet device when connected to a PC
You can SSH directly using the hostname you set in Raspberry Pi Imager — no Wi-Fi or Ethernet setup required
If your PC has an active internet connection and ICS is enabled, the Raspberry Pi will automatically receive internet access through the same USB cable
A lightweight background service runs on the Raspberry Pi to detect host connectivity and automatically switch between standalone mode and ICS-backed networking
In practice, it behaves very similarly to USB tethering on a smartphone — but for Raspberry Pi
The package is supported on all major host systems: Windows, macOS, and Linux.
Important hardware note
To use USB gadget mode, the Raspberry Pi must be connected to a USB port that supports OTG (device mode):
Raspberry Pi model
USB port to use
Raspberry Pi Zero, Zero W, Zero 2 W
The micro USB port closest to HDMI — not ‘PWR IN’
Raspberry Pi 4, 5, 500, 500+
The USB-C port directly on the board
Compute Module 5
The USB-C port on the Raspberry Pi CM5 IO Board
Compute Module 4
Requires additional manual setup and is not auto-configured
⚠ Warning:
Once gadget mode is enabled, the selected port will function exclusively as USB networking + power input; it will no longer operate as a regular USB host port. This means that keyboards, storage devices, or other peripherals cannot be connected to that port while gadget mode is active.
Supported boards:
Raspberry Pi Zero (W) and Zero 2 W
Raspberry Pi 3 Model A+
Raspberry Pi 4 Model B
Raspberry Pi 5, 500, and 500+
Compute Module 5
Compute Module 4 (technically supported, but additional manual setup is required)
For optimal stability — especially on Raspberry Pi 4, 5, and 500/500+ — connect the Raspberry Pi directly to a USB port on your PC. Some laptop USB ports cannot provide sufficient power, which may cause reboots or USB link drops.
Recommended accessory: The Raspberry Pi USB 3 Hub allows you to power the device externally while still passing only data over the USB connection; this is ideal for laptops with weak USB power delivery.
Enabling gadget mode the easy way: Raspberry Pi Imager 2.0
Double-click the generated os_list_local.rpi-imager-manifest file
Select a Raspberry Pi OS Trixie image (20.10.2025 or newer)
In the ‘Customisation’ menu, set a hostname
This is the name you’ll use to SSH into the Raspberry Pi
If ICS is disabled on the host, the fallback IP will be 10.12.194.1
Go to ‘Interfaces & Features’ and toggle ‘Enable USB Gadget Mode’
Write the image, insert the card into your Raspberry Pi, and connect it to your PC using the correct USB/OTG port (not just the power input)
Power on the Raspberry Pi (the first boot may take longer than usual and might reboot once — this is expected)
Once booted, your Raspberry Pi should appear as a new Ethernet adapter on your host machine
You can now SSH using the hostname you set
Windows driver requirement
Windows does not include a generic driver for USB Ethernet gadget devices. To avoid relying on impersonated vendor IDs or unofficial drivers, a dedicated installer is provided: download and run rpi-usb-gadget-driver-setup.exe from the project’s releases page on GitHub.
This only needs to be done once per Windows machine.
Internet Connection Sharing (ICS)
If you want your Raspberry Pi to access the internet through the USB connection, enable Internet Connection Sharing (ICS) on your host computer.
On Windows
Plug in the Raspberry Pi and confirm it shows up as a new Ethernet adapter
→ It will appear under a name like ‘Ethernet 7 — Raspberry Pi USB Remote NDIS Network Device’
Open ‘Network Connections’:
→ Control Panel → Network and Internet → Network and Sharing Center → Change adapter settings
→ Or press Win + R and enter ncpa.cpl
Identify your primary internet-connected adapter (e.g. Wi-Fi) and open ‘Properties’
Go to the ‘Sharing’ tab, enable ‘Allow other network users to connect…’, and, in the dropdown, choose the Raspberry Pi USB Ethernet adapter
Confirm your selection; within around 60 seconds, the Raspberry Pi should obtain an IP address
⚠ Note on Windows ICS behavior:
If ICS is enabled for the Raspberry Pi’s adapter while the Raspberry Pi is not connected, Windows may bind its DHCP service to another interface (such as a Hyper-V adapter). In that case, the Raspberry Pi interface may show as shared but will not receive a DHCP lease. To fix this, fully disable ICS on all adapters you shared the network from, plug in the Raspberry Pi, and then re-enable ICS.
On macOS
Connect the Raspberry Pi and wait for it to appear as a new USB Ethernet device
Open System Settings → General → Sharing → Internet Sharing
Before enabling, click the info icon to configure:
→ Your internet source (e.g. Wi-Fi)
→ The Raspberry Pi USB Gadget interface as the target to share to
Save and toggle ‘Internet Sharing’ on
On Linux
Enable routing and NAT from your primary internet connection to the Raspberry Pi USB Gadget network interface using your distribution’s NetworkManager or equivalent. Instructions vary depending on the desktop environment or init system.
Enabling USB gadget mode without Imager
This only applies to Raspberry Pi OS Trixie–based images.
Fresh images (before first boot):
Cloud-init can enable USB gadget mode automatically on first boot:
Mount the boot partition
Edit user-data and append:
rpi:
enable_usb_gadget: true
enable_ssh: true # Optional but recommended when using gadget mode
It’s recommended that you also define a user and an SSH key in the same file, as the setup wizard cannot be used over SSH, and connecting USB peripherals is not possible on Zero boards while gadget mode is active.
Existing installation:
1. Verify that you are running Raspberry Pi OS Trixie:
After reboot, the USB port will switch into gadget mode. Any active SSH sessions will temporarily drop and then reconnect once the USB Ethernet interface becomes available. Depending on the host system, give it up to one minute for DHCP/ICS negotiation to settle.
Technical details
The rpi-usb-gadget package configures the g_ether USB gadget kernel module, which exposes a virtual Ethernet interface according to the host OS’ capabilities:
Windows hosts → RNDIS mode
macOS/Linux hosts → CDC-ECM mode
The correct mode is automatically selected at runtime based on USB descriptor negotiation — no manual selection is required.
Why no USB serial console?
CDC-ACM (serial over USB) is not included, as Windows cannot bind both RNDIS/ECM and ACM to a single composite USB device using one .inf file without vendor-specific drivers.
A lightweight background service runs on the Raspberry Pi and continuously monitors:
USB link state
DHCP/ICS availability on the host
Routing and DNS status
If ICS is detected on the host, gateway and DNS configurations are automatically applied to provide seamless internet access over USB.
Troubleshooting
If the connection doesn’t work immediately, work through the following checks:
Hardware and cabling
Ensure you are using the correct USB/OTG port:
→ On Zero models, this must be the port labeled USB, not PWR IN
Connect directly to a USB port on the host PC — avoid hubs or docks that may block OTG negotiation or limit power
Only connect one Raspberry Pi at a time in gadget mode to avoid host-side interface conflicts
If the Raspberry Pi reboots repeatedly or disconnects, it may not be receiving enough power
→ Use a powered USB hub or the Raspberry Pi USB 3 Hub to supply external power while keeping data routed through the host
ICS and DHCP behavior
After enabling ICS, wait up to one minute for DHCP to issue an IP, and for hostname resolution to begin working
On Windows, if the gadget adapter shows as ‘Shared’ but no IP is assigned:
→ Disable ICS completely on all interfaces, plug in the Raspberry Pi, then re-enable ICS and reassign the correct adapter
Windows may list multiple ‘Ethernet X’ adapters from previous attempts
→ Consider removing or disabling unused adapters to prevent routing conflicts
Hostname and mDNS
If ssh pi@hostname.local does not resolve on Windows, install Bonjour/mDNS support or use the assigned IP address directly (shown in arp -a)
Source code and driver downloads
This feature is now included by default in Raspberry Pi OS Trixie images, but all code and tooling remain open for inspection and contribution. You can find the full source, the documentation, and the Windows driver installer (rpi-usb-gadget-driver-setup.exe) here.
The repository also contains an issue tracker, as well as reports from real-world setups — particularly involving ICS on Windows and macOS — which are extremely valuable. Different host systems behave slightly differently when assigning DHCP, routing, or firewall rules, so community feedback helps make the experience more reliable for everyone.
Wrapping up
USB gadget mode brings a Raspberry Pi much closer to being a plug-and-go development device — no Wi-Fi setup, no IP scanning, no HDMI, and no keyboard required. Just connect a single USB cable, SSH in, and start building.
This feature has been designed to be simple enough for beginners to use, yet robust and scriptable enough for power users and large-scale deployments. Future updates will continue to refine host detection, ICS handling, and diagnostics. If you have ideas or edge cases to share, the GitHub issue tracker and the Raspberry Pi Forums are open.
A little over a year ago, we introduced the Raspberry Pi AI HAT+, an add-on board for Raspberry Pi 5 featuring the Hailo-8 (26-TOPS variant) and Hailo-8L (13-TOPS variant) neural network accelerators. With all AI processing happening directly on the device, the AI HAT+ delivered true edge AI capabilities to our users, giving them data privacy and security while eliminating the need to subscribe to expensive cloud-based AI services.
While the AI HAT+ provides best-in-class acceleration for vision-based neural network models, including object detection, pose estimation, and scene segmentation (see it in action here), it lacks the capability to run the increasingly popular generative AI (GenAI) models. Today, we are excited to announce the Raspberry Pi AI HAT+ 2, our first AI product designed to fill the generative AI gap.
Unlock generative AI on your Raspberry Pi 5
Featuring the new Hailo-10H neural network accelerator, the Raspberry Pi AI HAT+ 2 delivers 40 TOPS (INT4) of inferencing performance, ensuring generative AI workloads run smoothly on Raspberry Pi 5. Performing all AI processing locally and without a network connection, the AI HAT+ 2 operates reliably and with low latency, maintaining the privacy, security, and cost-efficiency of cloud-free AI computing that we introduced with the original AI HAT+.
Unlike its predecessor, the AI HAT+ 2 features 8GB of dedicated on-board RAM, enabling the accelerator to efficiently handle much larger models than previously possible. This, along with an updated hardware architecture, allows the Hailo-10H chip to accelerate large language models (LLMs), vision-language models (VLMs), and other generative AI applications.
For vision-based models — such as Yolo-based object recognition, pose estimation, and scene segmentation — the AI HAT+ 2’s computer vision performance is broadly equivalent to that of its 26-TOPS predecessor, thanks to the on-board RAM. It also benefits from the same tight integration with our camera software stack (libcamera, rpicam-apps, and Picamera2) as the original AI HAT+. For users already working with the AI HAT+ software, transitioning to the AI HAT+ 2 is mostly seamless and transparent.
Some example applications
The following LLMs will be available to install at launch:
Model
Parameters/size
DeepSeek-R1-Distill
1.5 billion
Llama3.2
1 billion
Qwen2.5-Coder
1.5 billion
Qwen2.5-Instruct
1.5 billion
Qwen2
1.5 billion
More (and larger) models are being readied for updates, and should be available to install soon after launch.
Let’s take a quick look at some of these models in action. The following examples use the hailo-ollama LLM backend (available in Hailo’s Developer Zone) and the Open WebUI frontend, providing a familiar chat interface via a browser. All of these examples are running entirely locally on a Raspberry Pi AI HAT+ 2 connected to a Raspberry Pi 5.
The first example uses the Qwen2 model to answer a few simple questions:
The next example uses the Qwen2.5-Coder model to perform a coding task:
This example does some simple French-to-English translation using Qwen2:
The final example shows a VLM describing the scene from a camera stream:
Fine-tune your AI models
By far the most popular examples of generative AI models are LLMs like ChatGPT and Claude, text-to-image/video models like Stable Diffusion and DALL-E, and, more recently, VLMs that combine the capabilities of vision models and LLMs. Although the examples above showcase the capabilities of the available AI models, one must keep their limitations in mind: cloud-based LLMs from OpenAI, Meta, and Anthropic range from 500 billion to 2 trillion parameters; the edge-based LLMs running on the Raspberry Pi AI HAT+ 2, which are sized to fit into the available on-board RAM, typically run at 1–7 billion parameters. Smaller LLMs like these are not designed to match the knowledge set available to the larger models, but rather to operate within a constrained dataset.
This limitation can be overcome by fine-tuning the AI models for your specific use case. On the original Raspberry Pi AI HAT+, visual models (such as Yolo) can be retrained using image datasets suited to the HAT’s intended application — this is also the case for the Raspberry Pi AI HAT+ 2, and can be done using the Hailo Dataflow Compiler.
Similarly, the AI HAT+ 2 supports Low-Rank Adaptation (LoRA)–based fine-tuning of the language models, enabling efficient, task-specific customisation of pre-trained LLMs while keeping most of the base model parameters frozen. Users can compile adapters for their particular tasks using the Hailo Dataflow Compiler and run the adapted models on the Raspberry Pi AI HAT+ 2.
Available to buy now
The Raspberry Pi AI HAT+ 2 is available now at $130. For help setting yours up, check out our AI HAT guide.
Hailo’s GitHub repo provides plenty of examples, demos, and frameworks for vision- and GenAI-based applications, such as VLMs, voice assistants, and speech recognition. You can also find documentation, tutorials, and downloads for the Dataflow Compiler and the hailo-ollama server in Hailo’s Developer Zone.
Keeping tabs on cattle ranging over enormous ranches in rural Canada is a serious challenge. “Ranching operates outdoors, in all weather, in remote locations where there is no power or data connectivity,” explains Flokk founder and CEO Mark Olson. Record-keeping has traditionally been done using pocket notebooks, which are easily lost, damaged or trampled underfoot while the rancher struggles to check on each animal’s health and well-being. It’s the sort of task that hapless TV vets might have nightmares about. Nonetheless, detailed and fully up-to-date information about each cow is mandatory in the highly regulated world of animal husbandry.
Flokk’s ruggedised handheld scanner records crucial animal data;
details are saved to a Raspberry Pi Zero W inside and sent to a central server via Starlink satellite broadband
Computer scientist and farmer Mark Olson applied his knowledge of data collection to address the issue, coming up with a ruggedised scanner that has a Raspberry Pi Zero W at its heart and which automates much of the record collection process.
Rural reach
Mark grew up on a farm in Alberta, Canada, and, after briefly exploring the computerisation of agriculture when he graduated in the mid-1980s, went on to work in enterprise IT and management. Open-source software has always interested Mark, not least because his early forays into building home servers were of the DIY, fish-the-hardware-out-of-the-dumpster variety. Linux was the only platform he could afford that would run on the hardware he’d sourced. An interest in Raspberry Pi is therefore no surprise. It’s “a logical extension of my interest and aptitudes in open source,” says Mark, who uses Debian Linux for both Flokk’s website and online services.
RFID tags are read by the Flokk handheld scanner and the details are uploaded to a central database
This contrasts with “digital solutions for ranching [that] currently attempt to use hardware built for offices, not ranches. Consumer hardware is expensive and delicate, and unsuitable for the harsh environment of ranches.”
Traceability is not only desirable — it’s legally mandated. All Canadian cattle are fitted with a tag with an RFID code so that, if an issue arises with the animal, it can be traced back, and any other animals that might have been impacted by the issue can be located and investigated.
Flokk digitises data collection and record keeping for cow/calf ranching, a $5 billion industry in Canada and a trillion dollar industry globally, moving it from the small pocket notebooks ranchers use today to a digital solution.
Mark’s LinkedIn article about the importance of such record-keeping for the Canadian agricultural economy offers some valuable insights. He talks of the clear need for beef traceability and for Canada to secure its future food security via agricultural exports. He also emphasises the importance of keeping data (including saleability, individual animal traceability, pregnancy, and other health stats) on-device, freeing up the rancher’s time by giving them the autonomy that comes from not having to laboriously fill out paperwork. Ranchers can now capture data using in-field scans and have it digitised and stored immediately, keeping it safe.
Quick FACTS
Every livestock animal in Canada should have an in-ear RFID tag
Most ranchers have no means of reading the CCIA tags, so they keep paper records
Missing and inaccurate records impact traceability efforts
Dedicated digital readers are expensive and have no other functions
Flokk works with record management software, making compliance easier
He points out that Canada spends around 40% of its agricultural services budget on inspection and control, and says this could be massively reduced by using technology to tag and monitor agricultural assets. Starlink provides “a ready answer for rural broadband and wireless connectivity”, and he rates it above 5G connectivity, “which is both far more expensive to install and requires time to roll out, along with ongoing maintenance”.
No platform other than Debian — the flavour of Linux behind Raspberry Pi OS — lets you take the same software and skill set and apply it all the way from a battery-powered handheld, through an SBC desktop, to a multi-node server.
Hard-headed approach
Flokk chose Raspberry Pi for its affordability, high capability, and compatibility with other open-source products. “Raspberry Pi Zero W uses a full-function Broadcom system on a chip, not a microcontroller, and Linux as the OS, [so] Flokk can leverage standard open-source tools. We can add functionality in days and be confident our platform will support whatever software or functionality we will need to deliver in future.”
The ruggedised handset is ideal for ranchers on the move
It was important that the cost of the handheld scanners wouldn’t be a barrier to ranchers adopting them; Flokk will make its money from subscriptions, rather than the hardware. The end of life for a Flokk handheld will most likely not be the result of wear and tear or obsolescence — rather, it will be dropped into a pen of cattle and stomped on. Flokk has to be able to rapidly, and affordably, recover a customer’s data from offsite backup and ship them a new Flokk ready to use.
Mark wrote all the code himself, devoting more than 1000 hours to both code and platform development. When they began the process, Raspbian/Raspberry Pi OS would not run on the handheld scanner, so they used Tiny Core Linux instead. Future iterations may use this alongside Raspberry Pi OS.
Flokk runs Tiny Core Linux code on Raspberry Pi Zero W, alongside an RFID reader inside a Hammond Hand-Held T ruggedised case
Mark says Raspberry Pi Zero’s capabilities were “a perfect match; right price, power efficient, and exactly the I/O we needed”. Flokk is currently preparing its next iteration of hardware, migrating to Raspberry Pi Zero 2 W, upgrading the handheld scanner’s display, and adding a GPS receiver and, perhaps, a camera.
For now, Mark is busy garnering investor interest in Flokk so that it can be rolled out at scale across Canada’s ranches. Demonstrating its real-world use is imperative. “The Flokk I proudly use for investor presentations has brown stains on it; and the source of those brown stains is exactly what you think it is.”
This article is from Raspberry Pi Official Magazine #161
You can grab this issue from Tesco, Sainsbury’s, Asda, WHSmith, and other newsagents, including the Raspberry Pi Store in Cambridge. It’s also available from our online store, which ships around the world. And you can get a digital version via our app on Android or iOS.
You can also subscribe to the print version of our magazine. Not only do we deliver worldwide, but people who sign up to the six- or twelve-month print subscription get a FREE Raspberry Pi Pico 2 W!
At this time of year, lots of new Raspberry Pi users are wondering what to do with the tiny computer they were gifted at Christmas. The excellent team behind Raspberry Pi Official Magazine thought ahead and included a collection of fun, beginner-friendly projects for you to try in the latest issue. Happy #MakerMonday to all of our new friends.
Do citizen science with Raspberry Shake
Help map tremors around the world with this simple kit
This seismometer kit includes a special geophone sensor that lets you study the Earth and its movements very accurately. Not only that, but you can hook it up to a network of like-minded amateur — and professional — seismologists and see how seismic activity spreads around the world, in real time.
Add to a global network of citizen scientists monitoring seismic activity
Assembly is very easy — just connect the geophone to the add-on board, put the board on a Raspberry Pi, then assemble the acrylic case. There’s a handy video that runs you through the process, too, and goes on to cover the software setup.
The kit for Raspberry Shake is nice and compact
Monitor your plants with Pico
Get a text when your hydrangeas need some hydration
Home automation doesn’t just have to involve controlling your lights and heating — you can also use similar techniques to maintain your plants. Moisture sensors are a very common component for Raspberry Pi projects, and the Grow HAT from Pimoroni makes it easier to use them.
A Grow Kit monitors the soil moisture
The extra trick to this project is that it will send you emails with updates — inspiring messages in the morning, as well as reminders that your plant needs a bit of water. This project also makes use of a little hack to get a Raspberry Pi HAT to work with Pico — it uses a lot less power than a full Raspberry Pi too, making the project much greener.
A Perma-Proto HAT is used to connect Pico to the Grow HAT
Record stop-motion videos with a Camera Module
Become a movie-maker with some Lego and a lot of patience
We can show you how to take simple pictures or videos with a Raspberry Pi and a Camera Module, but we think it’s a lot more fun to create a hybrid setup that aids in stop-motion photography.
Orange you glad you made a film?
Very simply, this project lets you take a photo at the press of a button, and then waits for you to press the button again for the next photo. In that time, you rearrange what’s in the preview window on your monitor, creating a frame of animation each time. You can then stitch these together with some code to create a final product. With a few programming tricks, you can even have a ghostly version of the previous frame on screen to aid you in setting up the next shot.
Create a robot
Make a friendly automaton with a suite of custom sensors
The CamJam EduKit 3 is the perfect introduction to building your own robot. It’s a small and inexpensive kit that pairs with a full-size Raspberry Pi or Raspberry Pi Zero to create a customisable machine that you can either use as a remote-control car or to experiment with robot automation.
A 3D-printed chassis is available, but you can actually use the box from the kit to make the robot
It comes with an ultrasonic distance sensor and line followers — classic robotics sensors used for navigation. Assembly is fairly straightforward, and the Raspberry Pi Foundation’s tutorial even makes use of the box it comes in to build it; no parts wasted!
There are a lot of parts, but minimal soldering involved
Build a smart mirror
Check on yourself and your day with one futuristic piece of furniture
Smart mirrors, aka magic mirrors, are one of those projects that every Raspberry Pi maker needs to do once. On the surface, it may seem like a complex and advanced project; however, it’s actually fairly straightforward. The hardest part can be constructing the frame, which, if you can’t find a suitable pre-made frame at IKEA, involves a simple bit of carpentry.
There aren’t many components to a smart mirror
Putting some reflective two-way mirrored wrap on a big old TV and installing the Magic Mirror software are the other main steps; the latter is very easy to configure and has plenty of add-ons too.
A small IKEA frame with a compact monitor does the trick for a smaller version
This article is from Raspberry Pi Official Magazine #161
You can grab this issue from Tesco, Sainsbury’s, Asda, WHSmith, and other newsagents, including the Raspberry Pi Store in Cambridge. It’s also available from our online store, which ships around the world. And you can get a digital version via our app on Android or iOS.
You can also subscribe to the print version of our magazine. Not only do we deliver worldwide, but people who sign up to the six- or twelve-month print subscription get a FREE Raspberry Pi Pico 2 W!
Our friends over at Sixfab, one of our long-standing Raspberry Pi Design Partners, are kicking off 2026 in serious style. They headed to Las Vegas this week to pick up the CES Best of Innovation Award — the show’s highest honour — for their new AI gateway, ALPON X5 AI, which is powered by Raspberry Pi Compute Module 5 and DEEPX’s DX-M1 accelerator chip.
If you’ve ever needed to connect your Raspberry Pi to… well, just about anything, you’ve probably come across Sixfab’s gear. They’ve been making clever connectivity solutions for years: LTE and 5G modems, IoT shields, and the sort of industrial-ready bits and pieces that keep real-world deployments ticking without anyone having to duct-tape a USB dongle to a radio mast. (Not that we’re judging.)
Their award-winning ALPON X5 AI is an edge AI gateway designed for rugged deployments in the field — the kind where you need a full stack of compute, connectivity, and machine learning in one compact box. With Compute Module 5 and DX-M1 silicon under the hood, it’s built for low-power, high-performance inferencing at the edge, making it a strong fit for manufacturers rolling out smart kiosks, robotics, industrial automation solutions, or even that one remote sensor you’ve long since forgotten about somewhere on a hill in Wales.
Sixfab’s ALPON X5 AI brings:
High-efficiency AI acceleration thanks to DEEPX’s DX-M1 chip
Industrial-grade cellular and wired connectivity options
Drop-in support for Raspberry Pi–based workflows and deployments
A clean, developer-friendly software stack
We were at CES too; our very own Chris Boross and Samantha Snyder were on hand to celebrate Sixfab’s Best of Innovation win!
We’d like to extend a huge congratulations to the whole Sixfab team. They’ve been doing great stuff with Raspberry Pi for years, and it’s lovely to see them get this very shiny bit of recognition.
There are now hundreds of products with Raspberry Pi, in one form or another, at their centre. This includes consumer kit that promises exciting new project features, HATs and accessories for both hobbyist and industrial users, and specialist hardware versions with a Compute Module at the heart of their DNA. The Powered by Raspberry Pi stamp of approval helps assure you that a product has been thoroughly tested and is guaranteed to work flawlessly using Raspberry Pi computers and microcontrollers.
The latest issue of Raspberry Pi Official Magazine featured half a dozen products from around the world that are helping improve things like driver and passenger safety, drone pilots’ chances of a successful landing, and marine pilots’ navigation accuracy. There are also some treats for fans of vintage computers and gaming, as well as AI photography, in the section below.
Many of us love embracing older technology to enjoy games and programming experiences from a decade or three ago. Inevitably, the storage formats of the 1980s and 1990s have long been superseded, along with the drivers written to work with them. But that doesn’t mean you can’t run older programs, of course; emulators for popular home computers are incredibly popular. BlueSCSI offers a neat way to access games, applications, and files hidden away on otherwise-obsolete external drives so that you can enjoy them all over again. This modern, open source solution replaces your old SCSI drives — including CD-ROM and magneto-optical — with a simple and reliable SD card, offering a fantastic upgrade for your classic Mac, Amiga, Atari, and more!
Any full-size Raspberry Pi computer can be used to run Candera’s CGI Studio Professional HMI (human–machine interface). Its rapid design tools are custom-made for small-to-medium-sized businesses, and include an invaluable Scene Composer and pre-built players for Linux-based devices. Certified for Raspberry Pi, CGI Studio Pro offers Python scripting with data model access, making it ideal for designing user interfaces and customer menus for any number of applications. Version 3.15, launched in spring 2025, extends the IntuitiveHMI design suite with simplified workflows, improved graphics, and added AI options — including SoundHound voice recognition — making it ideal for designers creating interfaces across automotive, medical, and other industries.
Clickdrive is a driving training system aimed at driving schools and public transport companies, who have found it invaluable in improving staff retention rates. A self-install kit with wired and wireless options, GPS, and a HD video camera, Clickdrive makes real-world training more intuitive by recording driving footage, integrating features such as bespoke instructor clips, GPS and motion sensors for location accuracy, object detection, and performance analysis. While driving games and simulators focus on overcoming obstacles and taking turns at high speed, Clickdrive records routes driven for self-improvement rather than fun, using customisable training programmes. The Singapore-based company has a roster of satisfied clients, including the city’s own SBS Transit authority and other public transport companies. The Clickdrive PRO system provides 360-degree video feedback alongside objective driving telemetry analysis, so drivers can receive individual post-drive reviews and tailored improvement advice.
Flying machines have long caught the imagination of amateur pilots, so when drones arrived on the scene, their success was little surprise. If you’re anything like us, though, the joy of seeing your craft aloft is tinged with anxiety about the seemingly inevitable sudden descent back and the potential curtailment of your new hobby. Landmark specialises in helping PX4 and ArduPilot drone and model aircraft pilots achieve precision landings time after time. (OK, the clue’s in the company name.) Promising centimetre-level landing accuracy, the system works in various lighting conditions, including direct sunlight and at night (with target illumination). The landing module attaches to your Raspberry Pi via a single cable, while a ground station such as Mission Planner or QGroundControl is used for all configuration.
Raspberry Pi Compute Modules, with their industrial-grade specifications, are becoming an increasingly popular choice for marine applications. Finland’s Hat Labs is a long-established open source and open hardware marine specialist. As well as being a keen sailor, founder Matti is an IoT veteran with many years’ experience with CAN bus and NMEA 2000 products. The Helsinki-based firm’s HALPI2 is a marine plotting platform based around Compute Module 5 and an ITX motherboard in a custom-designed, pre-built, fully functional Raspberry Pi boat computer, protected within a waterproof and ruggedised case. HALPI2 plots and tracks routes and acts as a data acquisition and visualisation device, providing a large degree of boat automation and control.
EDATEC makes robust hardware based on open source principles, using powerful equipment such as Raspberry Pi. Emerging from the management team at industrial supplier Farnell in 2017, EDATEC was among the very first to recognise Raspberry Pi’s potential as a modular industrial platform — and one of the first to gain Powered by Raspberry Pi accreditation. The 12MP ED-AIC3100 uses Compute Module 5, with its 64-bit SoC platform, to power and control a quad-core AI camera with a 12mm autofocus liquid lens and a C-Mount lens. The 3100-series camera is protected by a bright blue IP65 shockproof metal case that can withstand temperature variations of 0–45°C, and has a mounting bracket to absorb vibrations. Running 64-bit Raspberry Pi OS, the AI camera weighs just 400g and can be triggered remotely or with a single button press, acquiring and processing images at 70 frames per second before efficiently making sense of their contents.
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The Raspberry Pi community is big on 3D printing, so in celebration of the first #MakerMonday of the new year, we thought we’d share this RP2040-powered scale that tells you whether or not you have enough filament for a 3D print.
If you’re going to use a 3D printer, you need to be sure that you have enough filament for the job. “Knowing if there is sufficient filament will tell you if you need a standby reel, a new reel, or whether the current reel will do the job,” says maker Chris Forde. One way to determine this is to weigh the filament remaining on the spool and compare it to the weight estimate provided by your slicing software. With this in mind, Chris came up with a solution.
The beam load cell is suitable for low to medium loads; the device is controlled by switches, and there are reset and boot buttons too
“Normally, when weighing filament, people use a separate scale and a calculator, but I thought it would be more convenient to integrate a filament scale into the printer,” he said. The idea was to replace the printer’s existing spool holder with one that contains a beam load cell. A beam load cell is a cantilever that measures applied force and converts it into an electrical signal, which can then be interpreted as weight.
“I identified a beam load cell with a maximum capacity of 5kg, although the filament reels to be used are 1kg, allowing a degree of overload protection,” Chris says. “My chosen load cell also came with a signal-conditioning amplifier which can be interfaced to a microcontroller.” This enabled him to combine the specialised transducer with an RP2040 microcontroller board, choosing one with an integrated LCD. “It allowed me to reduce the footprint, cost, and build time,” he adds.
Scaling up
With the beam load cell identified, Chris designed a 3D-printed spool holder for an Elegoo Neptune 4 Pro 3D printer. “The spool holder and the case were designed using BlocksCAD, with the screw thread designed using Tinkercad,” he said. Once all the elements were printed, he was able to assemble the scale arm, which also incorporated an HX711 ADC load cell conditioning amplifier designed for weighing scales.
The assembled main unit includes a clear window to protect the RP2040 microcontroller board
Chris also custom-made a PCB onto which he could mount an RP2040 microcontroller board. “I opted for a PCB designed using EAGLE to mount the components, improving repeatability and reproducibility, and creating a robust project,” he explains.
With the main unit assembled, he turned his attention to the software, which he wrote in MicroPython v1.15 using the Thonny IDE.
Weighty issues
To work, the software needs a bunch of information. First, it requires the calibration value. “Calibration is important to ensure the scale displays the correct weight, and this is accomplished using a known weight,” Chris explains. The software also needs the baseline weight, as well as information about the filament material: its density (g/cm3), diameter (mm), and the weight of the empty reel (g).
The PCB is fitted with an HX711 ADC and headers for an RP2040 microcontroller board
“A small list of this information is held internally and within text files, either of which may be edited to extend or amend the lists,” Chris says. “The user needs to select the correct details … and, with all this information, weight and filament length can be calculated.”
The LCD instructs the user to perform any necessary tasks, such as removing the spool to capture the unladen weight. It also displays the required result, including the length in metres and weight in grams. Given the low cost of the parts, it’s already proven to be an efficient money- and waste-saving device. With full instructions and printable files on Hackster.io, it’s a project that many makers are sure to find useful.
This article is from Raspberry Pi Official Magazine #161
You can grab this issue from Tesco, Sainsbury’s, Asda, WHSmith, and other newsagents, including the Raspberry Pi Store in Cambridge. It’s also available from our online store, which ships around the world. And you can get a digital version via our app on Android or iOS.
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