It’s Official! The Raspberry Pi Is Now 10!

In any given field there are epoch-defining moments, those events after which nothing was quite the same as it had been before. It’s been a decade since the launch of the first Raspberry Pi single board computer. This was by no means the first inexpensive computer board, nor was it the first to support the GNU/Linux operating system, but it was among the first to promise a combination of those two. Coupled with support from a crop of British 8-bit alumni meant that from when it first gained publicity in early 2011 it garnered a huge buildup of interest.

We were first teased with a USB stick style prototype, which morphed into a much larger Raspberry Pi alpha board and finally into pre-production boards much closer to the model launched at the end of February ten years ago.

How To Disappoint Every Single British Geek At 6 AM

An array of Pi prototype boards pictured on display at the Cambridge University Computer Laboratory.
An array of Pi prototype boards pictured on display at the Cambridge University Computer Laboratory.

Pedants will claim that the 10th birthday of the Pi is technically not yet upon us because those first Model B boards went on sale on the 29th of February 2012, a leap day. The two distributors, RS and Farnell, were both putting them on sale with the expectation of selling around 10,000 units — a prediction that proved woefully inadequate, with both websites collapsing under the weight of would-be Pi-purchasers within seconds of opening up at 6 AM.

I was ready to order at 6 AM, and was only able to order mine halfway through the day. That short wait would be just the beginning — because they received so many more orders than anticipated, the bulk of the orders weren’t fulfilled until May. Nobody had imagined how wildly successful the Pi boards would become. Continue reading “It’s Official! The Raspberry Pi Is Now 10!”

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Hackaday Links: February 27, 2022

If there’s one thing that can trigger people, it’s the printer racket. Printer manufacturers who put DRM-like features into their consumables are rightly viewed as Satan’s spawn, and while these monsters have been content so far to only put digital rights management features into their ink and toner cartridges, they appear to now have their rapacious gaze set on print media too. At least according to the good folks over at the Electronic Frontier Foundation, who claim that Dymo’s latest generation of label printers will have RFID tags in the label cartridges, apparently to prevent consumers from buying non-Dymo media. The company doesn’t bill it as a way to lock you into their exorbitantly priced consumables, of course; rather, this is an exciting new feature that’s called “Automatic Label Recognition,” which keeps track of what labels are installed and how many are left. Of course, this is just red meat to people like us, and we fully expect to see workarounds in the not-to-distant future.

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Wordle bot

Solving Wordle By Adding Machine Vision To A 3D Printer

Truth be told, we haven’t jumped on the Wordle bandwagon yet, mainly because we don’t need to be provided with yet another diversion — we’re more than capable of finding our own rabbit holes to fall down, thank you very much. But the word puzzle does look intriguing, and since the rules and the interface are pretty simple, it’s no wonder we’ve seen a few efforts like this automated Wordle solver crop up lately.

The goal of Wordle is to find a specific five-letter, more-or-less-common English word in as few guesses as possible. Clues are given at each turn in the form of color-coding the letters to indicate whether they appear in the word and in what order. [iamflimflam1]’s approach was to attach a Raspberry Pi camera over the bed of a 3D printer and attach a phone stylus in place of the print head. A phone running Wordle is placed on the printer bed, and Open CV is used to find both the screen of the phone, as well as the position of the phone on the printer bed. From there, the robot uses the stylus to enter an opening word, analyzes the colors of the boxes, and narrows in on a solution.

The video below shows the bot in use, and source code is available if you want to try it yourself. If you need a deeper dive into Wordle solving algorithms, and indeed other variant puzzles in the *dle space, check out this recent article on reverse engineering the popular game.

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A Hombrew Retro Laptop

We feel bad when we see a retrocomputer project and think, “Hey! That’s not that old.” But, usually, when we think about it, it really is. Take the Penkesu. It looks like one of the little organizer computers that were popular — ok — a long time ago.

Inside is a Raspberry Pi Zero 2W, a 7.9 inch 400×1280 screen and a 48-key mechanical keyboard. Unsurprisingly, the case is mostly 3D printed, but it does use Gameboy Advance SP hinges.

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Weather Station Predicts Air Quality

Measuring air quality at any particular location isn’t too complicated. Just a sensor or two and a small microcontroller is generally all that’s needed. Predicting the upcoming air quality is a little more complicated, though, since so many factors determine how safe it will be to breathe the air outside. Luckily, though, we don’t need to know all of these factors and their complex interactions in order to predict air quality. We can train a computer to do that for us as [kutluhan_aktar] demonstrates with a machine learning-capable air quality meter.

The build is based around an Arduino Nano 33 BLE which is connected to a small weather station outside. It specifically monitors ozone concentration as a benchmark for overall air quality but also uses an anemometer and a BMP180 precision pressure and temperature sensor to assist in training the algorithm. The weather data is sent over Bluetooth to a Raspberry Pi which is running TensorFlow. Once the neural network was trained, the model was sent back to the Arduino which is now capable of using it to make much more accurate predictions of future air quality.

The build goes into quite a bit of detail on setting up the models, training them, and then using them on the Arduino. It’s an impressive build capped off with a fun 3D-printed case that resembles an old windmill. Using machine learning to help predict the weather is starting to become more commonplace as well, as we have seen before with this weather station that can predict rainfall intensity.

IR Translator Makes Truly Universal Remote

Universal remotes are a handy tool to have around if you have many devices that would all otherwise have their own remote controls. Merging them all into a single device leads to less clutter and less frustration, but they are often not truly “universal” as some of them may not support every infrared device that has ever been built. If you’re in a situation like that it’s possible to build a truly universal remote instead, provided you have a microcontroller and a few infrared LEDs on hand.

This was the situation that [Matt] found himself in when his Amazon Fire TV equipment control feature didn’t support his model of speakers. To get around this he programmed an Arduino to essentially translate the IR codes from the remote and output a compatible set of codes to the speakers.This requires both an IR photodiode and an IR LED but little else other than the codes for the remote and the equipment in question. With that all set up and programmed into the Aruino, [Matt]’s remote is one step closer to being truly “universal”.

While [Matt] was able to make use of existing codes in the Arduino library, it is also possible to capture the codes required manually by pointing a remote at a photodiode and programming a microcontroller to capture the codes that you need. [Matt] used a Raspberry Pi to do this when debugging this project, but we’ve also seen this method used with a similar build which uses an ESP8266 to control an air conditioner via its infrared remote control capabilities.

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Breakbeats Courtesy Of The RP2040

While one often listens to songs or albums in full, sometimes you just want to lay down a simple beat. [todbot]’s latest project promises to do just that.

The build relies on a Raspberry Pi Pico or any other RP2040-based microcontroller board, and is programmed in CircuitPython. The PWM feature is used for audio output, and it’s loaded with different WAV samples of the classic “Amen” break.

Each measure, a random new sample is chosen and played, changing the beat. Even better, all the samples can loop, and they come in varying lengths, allowing them to overlap and lay over each other to add further depth to the mix. It’s a cinch to setup, as CircuitPython has an AudioMixer object built in.

Those wishing to tinker for themselves can find all the code and samples on Github. A build like this one is a great way to start learning about working with audio and music, after all. We’ve seen [todbot]’s work here before, too. Video after the break.

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