Memorialize Your Favorite Chips In Slate

There’s no point in denying it — if you’re a regular reader of Hackaday, you’ve almost certainly got a favorite chip. Some in the audience yearn for the simpler days of the 6502, while others spend their days hacking on modern microcontrollers like the ESP32 or RP2040. There are even some of you out there still reaching for the classic 555. Whatever your silicon poison, there’s a good chance the Macrochips project from [Jason Coon] has supersized it for you.

The original slate RP2040

The idea is simple: get a standard 100 mm x 100 mm (4″ x 4″) slate coaster, throw it in your laser engraver of choice, and zap it with a replica of a chip’s label. The laser turns the slate a light gray, which, when contrasted with the natural color of the slate, makes for a fairly close approximation of what the real thing looks like. To date, [Jason] has given more than 140 classic and modern chips the slate treatment. Though he’s only provided the SVGs for a handful of them, we’re pretty sure anyone with a laser at home will have the requisite skills to pull this off without any outside assistance.

The page credits a post from [arturo182] for the idea (Nitter), which pointed out a slate RP2040 hiding out on the corner of [Graham Sanderson]’s desk back in 2021. We just became aware of the trend when [Jason] posted his freshly engraved RP1 on Mastodon in honor of the release of the Raspberry Pi 5.

LabVIEW Abandons Mac After Four Decades

When National Instruments (NI) released LabVIEW in 1986 it only targeted the Macintosh, with ports to other platforms coming later on in the 1990s. Now, NI has announced that with the next version in 2024, LabVIEW will only be released for Linux and Windows, leaving behind Apple’s software platform after nearly four decades. The news was covered by Apple Insider, which cites a forum thread on the NI website in which the details of LabVIEW for macOS are discussed. This news comes on the heels of the announcement of Valve dropping macOS support with Counter Strike 2.

In both cases the issue at hand appears to be both a combination of a low user count (less than 1% of CS:GO players) and the complexity of using proprietary APIs (Cocoa, Metal, etc.) that have led to the decision to terminate the macOS releases. Not that macOS users aren’t used to app-related bloodbaths after losing all 32-bit applications back in 2019, but the trend of more high-profile applications and games not supporting the OS does seem to be ramping up.

Perhaps the only positive news here for people who bought into the Apple hardware ecosystem here is that Windows runs on M1/M2 Macs, and there is even an experimental Linux distribution in the form of Asahi Linux to conceivably dual-boot into for those applications that just don’t want to run on Apple’s OS.

Stretching The Flight Time On A Compressed Air Plane

[Tom Stanton] has been experimenting with compressed air motors on model aircraft for a good few years, but keeping them aloft (and intact) for more than a few seconds has proven a tough nut to crack. His latest design represents a breakthrough — pulling off an impressive 1 minute and 26 seconds flight on 4 liters of compressed air.

The model incorporates an enhanced engine design featuring an expanding seal on the piston, a concept inspired by the old Air Hogs toy plane. For the airframe, he constructed lightweight wings using 3D printed ABS ribs on a carbon spar and reinforcing rods, all of which were wrapped in heat shrink film. Additionally, [Tom] incorporated a thin balsa former along the leading edge of the wing to help maintain its shape. The fuselage is also composed of a carbon fiber tube, and is outfitted with printed fittings to install the wings, V-tail, RC electronics, and soda/air bottles. A hollow nylon bolt holds the two bottles together end-to-end while allowing the motor to be screwed directly onto the front bottle. To conserve weight, each of the two V-tail control surfaces are actuated by single cables linked to servos, with piano wire torsion springs in the hinges to maintain tension

Despite successful flights, [Tom]’s trials were not without challenges. One crash threatened severe damage to his airframe, but thanks to a central 3D printed bracket that absorbed most of the impact, total destruction was avoided. Similarly, a printed shaft saved his expensive carbon fiber propeller from being damaged during multiple landings, an outcome that led [Tom] to devise a readily replaceable consumable connector.

A second video after the break offers a behind-the-scenes insights into this project including some fascinating technical details. For more on this project’s history, take a look at the initial diaphragm engines and his attempts to make them fly.

Continue reading “Stretching The Flight Time On A Compressed Air Plane”

Burnt Resistor Sleuthing

You smell smoke and the piece of gear you are working on stops working, probably at an inopportune time. You open it up and immediately see the burned remains of a resistor. You don’t have the schematic, the Internet has nothing to say, and the markings on the resistor are burned away. What do you do? [Learn Electronics Repair] has some advice.

The resistor is probably open, but even if it isn’t, you can’t count on any measurement you make. The burning could easily change the value. The technique comes from comments on one of his earlier videos where he had such a burned resistor but was able to find the correct value. He decided to test the suggestion: cut away the burned resistor and measure the pieces that are left. It probably won’t give you the exact value, but it will get you in the ballpark.

So a rotary tool did the surgery, and you can see it all in the video below. We aren’t sure this method would work on every type of resistor you might encounter, and surface mount will also present special problems. However, if you are stabbing in the dark anyway, it won’t hurt to try.

Everyone knows the smoke that comes out is magic. Sometimes, you cut into components by necessity. Other times, it is for art’s sake.

Continue reading “Burnt Resistor Sleuthing”

Keeping Badgers At Bay With Tensorflow

Human-animal conflict is always a contentious issue, and finding ways to prevent damage without causing harm to the animals often requires creative solutions. [James Milward] needed a humane method to stop badgers and foxes from uprooting his garden, leading him to create the Furbinator 3000, a system that combines computer vision with audio deterrents..

[James] initially tried using scent repellents (which were ignored) and blocking access to his garden (resulting in more digging), but found some success with commercial ultrasonic audio repellent devices. However, these had to be manually turned off during the day to avoid annoying activation of the PIR motion sensors by [James] and his family, and the integrated solar panels couldn’t keep up with the load.

This presented a good opportunity to try his hand at practical machine vision. He already had a substantial number of sample images from the Ring cameras in his garden, which he turned into a functional TensorFlow Lite model with about 2.5 hours of training. He linked it with event-activated RTSP streams from his Ring cameras using the ring-mqtt library. To minimize false positives on stationary objects, he incorporated a motion filter into the processing pipeline. When it identifies a fox or badger with reasonable accuracy, it generates an MQTT event.

[James] modified the ultrasonic devices so they would react to these events using an ESP8266-based WeMos D1 Mini Pro development board and added an external 5 V power supply for sustained operation. All development was performed in a Docker container which simplified deployment on a Raspberry Pi 4.

After implementing the system, [James] woke up to the satisfying sight of his garden remaining untouched overnight, a victory that even earned him some coverage by the BBC.

Thanks for the tip [Laurent]!

Compact, Gesture-Based Remote Control Over Bluetooth

[AlexMiller11] shared a project for a DIY gesture-sensing remote control that acts like a Bluetooth keyboard, capable of controlling media and presentations on a computer with a high degree of accuracy.

The device recognizes eight different gestures and controls a host PC over Bluetooth.

The hardware is a Silicon Labs xG24 dev kit, a small IoT-focused board able to be powered by a CR2032 cell. Part of what makes it all work is the six-axis IMU sensor, but the rest is the software to interpret that data and figure out what motions the user is trying to do. That happens with a Neuton.AI model and SDK, a tiny but effective machine learning framework for small devices.

How does it actually work? The device acts as a Bluetooth HID, and gets connected to a PC in the same was as a regular Bluetooth keyboard. Once that’s done, recognized gestures are printed out the serial port as well as sent via Bluetooth to the host machine. Media can then be played, paused, volume adjusted, presentations controlled, and more. More details are on the project’s GitHub repository. There’s also a demo video that explains exactly what’s going on, embedded below the page break.

Machine learning is a way of using software to solve the kinds of problems humans are not very good at writing programs to solve, and accurate gesture recognition is a good example. Not all such applications require heaps of overheating GPUs, either. We’ve seen the concept of a neural network stripped down to its bare essentials running on an Arduino Uno, for those who would like to better appreciate the fundamentals.

Continue reading “Compact, Gesture-Based Remote Control Over Bluetooth”

AI-Powered Snore Detector Shakes The Pillow So You Won’t

If you snore, you’ll probably find out about it from someone. An elbow to the ribs courtesy of your sleepless bedmate, the kids making fun of you at breakfast, or even the lady downstairs calling the cops might give you the clear sign that you rattle the rafters, and that it’s time to do something about it. But what if your snores are a bit more subtle, or you don’t have someone to urge you to roll over? In that case, this AI-powered haptic snore detector might be worth building.

The most distinctive characteristic of snoring is, of course, its sound, and that’s exactly what [Naveen Kumar] chose as a trigger. To differentiate between snoring and other nighttime sounds, [Naveen] chose an Arduino Nicla Voice sensor board, which sports a Syntiant NDP120 deep-learning processor and a built-in MEMS microphone. To generate a model that adequately represents the full tapestry of human snores, a publicly available snoring dataset — because of course that’s a thing — was used for training. Importantly, the training data included samples of non-snoring sounds, like sirens and thunder, as well as clips of legit snoring mixed with these other sounds. The model is trained with an online tool and downloaded onto the board; when it detects the sweet sound of sawing wood three times in a row, a haptic driver board vibrates the pillow as a gentle reminder to reposition. Watch it in action in the brief video below.

Snoring is something that’s easy to make light of, but in all seriousness, it’s not something to be taken lightly. Hats off to [Naveen] for developing a tool like this, which just might let you know you’ve got a problem that bears a closer look by a professional. Although it might work better as a wearable rather than a pillow-shaker.

Continue reading “AI-Powered Snore Detector Shakes The Pillow So You Won’t”