What Next For The SBC That Has Everything?

In the decade-and-a-bit since the first Raspberry Pi was launched we’ve seen an explosion of affordable single-board computers (SBCs), but as the prices creep up alongside user expectation and bloat, [Christopher Barnatt] asks where the industry will go next.

The Pi started with an unbeatable offer, $35 got you something similar to the desktop PC you’d had a decade earlier — able to run a Linux desktop on your TV from an SD card. Over the years the boards have become faster and more numerous, but the prices for ARM boards are now only nominally as affordable as they were in 2012, and meanwhile the lower end of x86 computing is now firmly in the same space. He demonstrates how much slower the 2023 Raspberry Pi OS distribution is on an original Pi compared to one of the early pre-Raspbian distros, and identifies in that a gap forming between users. From that he sees those people wanting a desktop heading towards the x86 machines, and the bare-metal makers at the lower end heading for the more powerful microcontrollers which simply weren’t so available a decade ago.

We have to admit that we agree with him, as the days when a new Raspberry Pi board was a special step forward rather than just another fast SBC are now probably behind us. In that we think the Pi people are probably also looking beyond their flagship product, as the hugely successful lunches of the RP2040 and the industrial-focused Compute Module 4 have shown.

What do you think about the SBC market? Tell us in the comments.

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JITX Spits Out Handy USB Cable Tester

When USB first came on the scene, one of the benefits was that essentially any four conductors could get you to the point where you could send information at 12 Mbps. Of course everything is faster these days, and reaching today’s speeds requires a little bit more fidelity in the cables. This simple tester makes sure that your modern cables are actually up to the task.

One of the design goals of this project is to automate away the task of testing cables or finding one that works, especially before thinking a problem with a device is somewhere in software, spending hours or days debugging, before realizing that it’s actually being caused by a hardware malfunction. The small PCB has two USB-C fittings to plug in both of the ends of a cable to, and between those connectors there is a number of LEDs. Each LED is paired to one the many conductors within the USB cable, and not only does it show continuity of these conductors but it can also show a high resistance connection via a dimly-lit or off-color display from an LED.

One of the other interesting facets of this build is the use of JITX, which is a software-defined electronics CAD tool which allows PCB design to be automated by writing out the requirements of the PCB into code, rather than drawing it manually. It’s worth a look, and a lot of the schematics of this particular project as well as some discussion on this software can be found on the project’s GitHub page. Incidentally, if this tester looks familiar, it’s probably because your’re thinking of the open source hardware USB tester created by [Álvaro Prieto].

Secret Bookshelf Door Uses Hidden Fingerprint Scanner

What is it that compels us about a secret door? It’s almost as if the door itself and the promise of mystery is more exciting than whatever could lay beyond. In any case, [Scott Monaghan] is a lover of the form, and built his own secret door hidden in a bookshelf, as all good secret doors should be.

The door is activated by pulling down on the correct book. This then reveals a fingerprint scanner. Upon presenting the right digit, the door will elegantly swing open to reveal the room beyond. Secret door experts will note there’s an obvious tell due to the light spilling through the cracks, however [Scott] reports that the finishing stages of the build solved this issue. The door was also fitted with a manual release for easier daily use.

Details are light, but the basics are all there. Really all you need is a cheap hardware store door opener, a secret activation lever or authentication method, and a well-hinged bookcase to achieve this feat yourself. We’ve seen some other great secret doors before, too. Video after the break.

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Simple Cubes Show Off AI-Driven Runtime Changes In VR

AR and VR developer [Skarredghost] got pretty excited about a virtual blue cube, and for a very good reason. It marked a successful prototype of an augmented reality experience in which the logic underlying the cube as a virtual object was changed by AI in response to verbal direction by the user. Saying “make it blue” did indeed turn the cube blue! (After a little thinking time, of course.)

It didn’t stop there, of course, and the blue cube proof-of-concept led to a number of simple demos. The first shows off a row of cubes changing color from red to green in response to musical volume, then a bundle of cubes change size in response to microphone volume, and cubes even start moving around in space.

The program accepts spoken input from the user, converts it to text, sends it to a natural language AI model, which then creates the necessary modifications and loads it into the environment to make runtime changes in Unity. The workflow is a bit cumbersome and highlights many of the challenges involved, but it works and that’s pretty nifty.

The GitHub repository is here and a good demonstration video is embedded just under the page break. There’s also a video with a much more in-depth discussion of what’s going on and a frank exploration of the technical challenges.

If you’re interested in this direction, it seems [Skarredghost] has rounded up the relevant details. And should you have a prototype idea that isn’t necessarily AR or VR but would benefit from AI-assisted speech recognition that can run locally? This project has what you need.

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Pretty Small Robot Is Capable, Nonetheless

When science fiction authors imagined robots in the 20th century, many of them were huge imposing steel automatons. [Shane]’s designs for the Pretty Small Robot are quite contrary to that, being tiny in stature and cute in affect.

The whole robot is an exploration in nifty engineering. It uses an easy clip-together structure with fasteners and glue not required. The chassis is 3D printed, with all the components sliding into place. Two small DC gearmotors are used for differential drive, with each side of the robot having a pair of wheels wrapped in a rubber band for traction. The brains of the robot is an ESP32, providing it with both plenty of processing power and good connectivity options. Control is over WiFI via MQTT.

At this stage the robot doesn’t do a whole lot, though [Shane] has some exciting plans. He’d like to add a camera in future and let it explore a maze under human command.

If you’ve ever wanted to build a robot with an almost coin-sized foot print, this build is for you. Files are available on GitHub for those wishing to dive deeper. Video after the break.

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Ultimate Garage Door Control Does The Job Brilliantly

[Stephen Carey] had previously relied on an Insteon garage door controller, only to have it perform poorly and fail at integrating with Alexa properly. Thus, he did what any good hacker would do, and built his own system instead.

The garage door was first outfitted with a pair of reed switches to sense when it was fully open or fully closed. The drive sprocket of the garage door was also set up to be monitored with magnets and Hall effect sensors, essentially creating a rotary encoder. This allows a ESP32 to monitor the door’s direction of travel, it’s position, and when it has hit the end stop in either direction. Using Micropython, [Stephen] whipped up some code to tie the garage door controls in with Home Assistant, complete with a neat visual display of the current door position.

There are millions of home automation products out there, many of which make annoying compromises that frustrate the end user. Sometimes, doing it your own way is the only way to get satisfaction!

Hackaday Prize 2023: EyeBREAK Could Be A Breakthrough

For those with strokes or other debilitating conditions, control over one’s eyelid can be one of the last remaining motor functions. Inspired by [Jeremiah Denton] blinking in Morse code on a televised interview, [MBW] designed an ESP32-based device to decode blinks into words.

While an ESP32 offers Bluetooth for simulating a keyboard and has a relatively low power draw, getting a proper blink detection system to run at 20 frames per second in a constrained environment is challenging. Earlier attempts used facial landmarks to try and determine, based on ratios, whether an eye was open or closed. A cascade detector combined with an XGBoost classifier offered excellent performance but struggled when the eye wasn’t centered. Ultimately a 50×50, 4-layer CNN in TensorFlow Lite processes the camera frames, producing a single output, eye open or closed. For debugging purposes, it streams camera frames over Wi-Fi with annotations via OpenCV, though getting OpenCV to compile for ESP32 was also nontrivial.

[MBW] trained the model using the MRL dataset and then quantized to int8. Getting the Bluetooth and Wi-Fi stacks to run concurrently was a bit of a pain, as was managing RAM. After exhausting SRAM and IRAM, [MBW] had to move to PRAM. The entire system is built into some lightweight goggles and makes for a fairly comfortable experience.

While TensorFlow and microcontrollers might seem like a bit of an odd couple, at the end of the day, the inference engine is just doing some math on an array of inputs with some weights. We’ve even seen TensorFlow Lite on a Commodore 64. If you don’t know about [Admiral Jerimiah Denton] we can shed some light on it for you.

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