Real-Time ISS Tracker Shows Off The Goods

March 9, 2026 by Tom Nardi 9 Comments

What hardware hacker doesn’t have a soft spot for transparent cases? While they may have fallen out of mainstream favor, they have an undeniable appeal to anyone with an interest in electronic or mechanical devices. Which is why the Orbigator built by [wyojustin] stands out among similar desktop orbital trackers we’ve seen.

Conceptually, it’s very similar to the International Space Station tracking lamp that [Will Dana] built in 2025. In fact, [wyojustin] cites it specifically as one of the inspirations for this project. But unlike that build, which saw a small model of the ISS moving across the surface of the globe, a transparent globe is rotated around the internal mechanism. This not only looks gorgeous, but solves a key problem in [Will]’s design — that is, there’s no trailing servo wiring that needs to be kept track of.

For anyone who wants an Orbigator of their own, [wyojustin] has done a fantastic job of documenting the hardware and software aspects of the build, and all the relevant files are available in the project’s GitHub repository.

The 3D printable components have been created with OpenSCAD, the firmware responsible for calculating the current position of the ISS on the Raspberry Pi Pico 2 is written in MicroPython, and the PCB was designed in KiCad. Incidentally, we noticed that Hackaday alum [Anool Mahidharia] appears to have been lending a hand with the board design.

As much as we love these polished orbital trackers, we’ve seen far more approachable builds if you don’t need something so elaborate. If you’re more interested in keeping an eye out for planes and can get your hands on a pan-and-tilt security camera, it’s even easier.

Last Year In SBCs

March 9, 2026 by Al Williams 7 Comments

While it might not be comprehensive, [Bret.dk] recently posted a retrospective titled “Every Single Board Computer I Tested in 2025.” The post covers 15 boards from 8 different companies. The cheapest board was $42, but the high-end topped out at $590.

We like the structure of the post. The boards are grouped in an under $50 category, another group for $50-100, and a final group for everything north of $100. Then there’s some analysis of what RAM prices are doing to the market, and commentary about CIX P1, Qualcomm, RISC-V, and more.

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Building A Heading Sensor Resistant To Magnetic Disturbances

March 6, 2026 by Zoe Skyforest 10 Comments

Light aircraft often use a heading indicator as a way to know where they’re going. Retired instrumentation engineer [Don Welch] recreated a heading indicator of his own, using cheap off-the-shelf hardware to get the job done.

The heart of the build is a Teensy 4.0 microcontroller. It’s paired with a BNO085 inertial measurement unit (IMU), which combines a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer into a single package. [Don] wanted to build a heading indicator that was immune to magnetic disturbances, so ignored the magnetometer readings entirely, using the rest of the IMU data instead.

Upon startup, the Teensy 4.0 initializes a small round TFT display, and draws the usual compass rose with North at the top of the display. Any motion after this will update the heading display accordingly, with [Don] noting the IMU has a fast update rate of 200 Hz for excellent motion tracking. The device does not self-calibrate to magnetic North; instead, an encoder can be used to calibrate the device to match a magnetic compass you have on hand. Or, you can just ensure it’s already facing North when you turn it on.

Thanks to the power of the Teensy 4.0 and the rapid updates of the BNO085, the display updates are nicely smooth and responsive. However, [Don] notes that it’s probably not quite an aircraft-spec build. We’ve featured some interesting investigations of just how much you can expect out of MEMS-based sensors like these before, too.

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AI Assistant Uses ESP32

February 27, 2026 by Al Williams 21 Comments

Having an AI assistant is all the rage these days, but AI assistants usually don’t know about your automation setups and may have difficulty dealing with tasks asynchronously. Enter zclaw. It gives you the option to have a personal assistant on an ESP32 backed by Anthropic, OpenAI, or OpenRouter. The whole thing fits in 888KB, and while it doesn’t host the LLM, it does add key capabilities to monitor and control devices connected to the ESP32.

You communicate with the assistant via telegram. You can say things like “Remember the garage sensor is on GPIO 4.” Then later you might say: “In 20 minutes, check the garage sensor and if it is high, set GPIO 5 low.” It has an RTOS for scheduling tasks and is aware of the timezone and common periods. Memory persists across reboots, and you can pick different personas.

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Random Number Generator Uses Camera Noise

February 25, 2026 by Zoe Skyforest 17 Comments

Random numbers are very important to us in this computer age, being used for all sorts of security and cryptographic tasks. [Theory to Thing] recently built a device to generate random numbers using nothing more complicated than simple camera noise.

The heart of the build is an ESP32 microcontroller, which [Theory to Thing] first paired with a temperature sensor as a source of randomness. However, it was quickly obvious that a thermocouple in a cup of tea wasn’t going to produce nice, jittery, noisy data that would make for good random numbers. Then, inspiration struck, when looking at vision from a camera with the lens cap on. Particularly at higher temperatures, speckles of noise were visible in the blackness—thermal noise, which was just what the doctor ordered.

Thus, the ESP32 was hooked up to an OV3660 camera, which was then covered up with a piece of black electrical tape. By looking at the least significant bits of the pixels in the image, it was possible to pick up noise when the camera should have been reporting all black pixels. [Theory to Thing] then had the ESP32 collate the noisy data and report it via a web app that offers up randomly-generated answers to yes-or-no questions.

[Theory to Thing] offers up a basic statistical exploration of bias in the system, and shows how it can be mitigated to some degree, but we’d love a deeper dive into the maths to truly quantify how good this system is when it comes to randomness. We’ve featured deep dives on the topic before.

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A TV Transmitter From An STM32

February 24, 2026 by Jenny List 8 Comments

Analog TV may have shuffled off its mortal coil years ago, but there are still plenty of old CRT TV sets around that could receive it. [Kris Slyka] has just such a device, and decided to feed it something from an STM32 microcontroller. An STM32G431, to be precise, and they’re doing it using the on-chip hardware rather than in software.

This unexpected feat is made possible by clever use of the internal oscillators and analog multiplexer. The video itself is generated using the MCU’s DAC, and fed into the on-board op-amp multiplexer which is switched at the VHF transmission frequency. This creates the required VHF TV transmission, but without audio. This component comes by abusing another peripheral, the internal RC oscillator for the USB. This is frequency modulated, and set to the required 5.5 MHz spacing from the vision carrier for the TV in question. It doesn’t (yet) generate the PAL color sub-carrier so for now it’s black and white only, but maybe someone will figure out a way.

We like unexpected out-of-spec uses of parts like these microcontrollers, and we especially like analog TV hereabouts. We marked its very final moments, back in 2021.

Pi Pico Learns Morse Code

February 10, 2026 by Al Williams 2 Comments

When [101 Things] didn’t want to copy Morse code, he decided to build a Pi Pico system to read it for him. On the face of it, this doesn’t seem particularly hard, until you look at the practical considerations. With perfectly timed dots and dashes, it would be trivial. But in real life, you get an audio signal. It has been mangled and mixed with noise and interference as it travels through the air. Then there’s the human on the other end who will rarely send at a constant speed with no errors.

Once you consider that, this becomes quite the project, indeed. The decoder captures audio via the Pi’s analog-to-digital converter. Then it resamples the input, applies an FFT, and converts the output via a complex classification pipeline that includes, among other things, Bayesian decoding. Part of the pipeline makes simple typo corrections. You can see the device do its thing in the video below.

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