Hardware projects often fall into three categories: Those that flash lights, those that make sounds and those that move. This virtuoso performance by [Kevin]’s “Lo-Fi Orchestra” manages all three, whilst doing an excellent job of reproducing the 1973 musical classic Tubular Bells by Mike Oldfield.

Producing decent polyphonic sounds of different timbres simultaneously is a challenge for simple microcontroller boards like Arduinos, so [Kevin] has embraced the “More is more” philosophy and split up the job of sound generation in much the same way as a traditional orchestra might. Altogether, 11 Arduino Nanos, 6 Arduino Unos, an Arduino Pro Mini, an Adafruit Feather 32u4, and a Raspberry Pi running MT32-Pi make up this electronic ensemble.

The servo & relay drumkit is a particular highlight, providing some physical sounds to go along with the otherwise solid-state generation.

The whole project is “conducted” over MIDI and the flashing sequencer in the middle gives a visual indication of the music that is almost hypnotic. The performance is split into two videos (after the break), and will be familiar to fans of 70’s music and classic horror movies alike. We’re astonished how accurately [Kevin] has captured the mood of the original recording.

If this all looks slightly familiar, it may be because we have covered the Lo-Fi Orchestra before, when it entertained us with a rousing rendition of Gustav Holst’s Planets Suite. If you’re more interested in real Tubular Bells than synthesized ones, then check out this MIDI-controlled set from 2013.

Typewriters may be long past their heyday, but just because PCs, word processor software, and cheap printers have made them largely obsolete doesn’t mean the world is better off without them. Using a typewriter is a rich sensory experience, from the feel of the keys under your fingers that even the clickiest of PC keyboards can’t compare with, to the weirdly universal sound of the type hitting paper.

So if life hands you a typewriter, why not put it back to work? That’s exactly what [Artillect] did by converting an 80s typewriter into a Linux terminal. The typewriter is a Brother AX-25, one of those electronic typewriters that predated word processing software and had a daisy wheel printhead, a small LCD display, and a whopping 8k of memory for editing documents. [Artillect] started his build by figuring out which keys mapped to which characters in the typewriter’s 8×11 matrix, and then turning an Arduino and two multiplexers loose on the driving the print head. The typewriter’s keyboard is yet used for input, as the project is still very much in the prototyping phase, so a Raspberry Pi acts as a serial monitor between the typewriter and a laptop. The video below has a good overview of the wiring and the software, and shows the typewriter banging out Linux command line output.

For now, [Artillect]’s typewriter acts basically like an old-school teletype. There’s plenty of room to take this further; we’d love to see this turned into a cyberdeck complete with a built-in printer, for instance. But even just as a proof of concept, this is pretty great, and you can be sure we’ll be trolling the thrift stores and yard sales looking for old typewriters.

If you’ve laid hands on a retro analog TV, have the restoration bug, and you plan to make the final project at least somewhat period-correct, you face a bit of a conundrum: what are you going to watch? Sure, you can serve up just about any content digitally these days, but some programs just don’t feel right on an old TV. And even if you do get suitably retro programming, streaming isn’t quite the same as the experience of tuning your way through the somewhat meager selections as we did back in the analog days.

But don’t worry — this Raspberry Pi TV simulator can make your streaming experience just like the analog TV experience of yore. It comes to us from [Rodrigo], who found a slightly abused 5″ black-and-white portable TV that was just right for the modification. The battery compartment underneath the set made the perfect place to mount a Pi, which takes care of streaming a variety of old movies and shorts. The position of the original tuning potentiometer is read by an Arduino, which tells the Pi which “channel” you’re currently tuned to.

Composite video is fed from the Pi’s output right into the TV’s video input, and the image quality is just about what you’d expect. But for our money, the thing that really sells this is the use of a relay to switch the TV’s tuner back into the circuit for a short bit between channel changes. This gives a realistic burst of static and snow, just like we endured in the old days. Hats off to [Rodrigo] for capturing everything that was awful about TV back in the day — Mesa of Lost Women, indeed! — but still managing to make it look good.

If you're taking your microcontroller or SBC project to market, these pluggable boards might be what you need.

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[Hal Rodriguez] and [Sahrye Cohen] of Amped Atelier focus on creating interactive wearable garments with some fairly high standards. Every garment must be pretty, and has to either be controllable by the wearer, through a set of sensors, or even by the audience via Bluetooth. Among their past creations are a dress with color sensors and 3D-printed scales on the front that change color, and a flowing pantsuit designed for a dancer using an accelerometer to make light patterns based on her movements.

Conductive Melody — a wearable musical instrument that is the focus of [Sahrye] and [Hal]’s Remoticon 2021 talk — was created for a presentation at Beakerhead Festival, a multi-day STEAM-based gathering in Calgary. [Sahrye] and [Hal] truly joined forces for this one, because [Sahrye] is all about electronics and costuming, and [Hal] is into synths and electronic music. You can see the demo in the video after the break.

The dress’s form is inspired by classical instruments and the types of clothing that they in turn inspired, such as long, generous sleeves for harp players and pianists. So [Hal] and [Sahrye] dreamed up a dress with a single large playable sleeve that hangs down from the mid- and upper arm. The sleeve is covered with laser-cut conductive fabric curlicues that look like a baroque interpretation of harp strings. Play a note by touching one of these traces, and the lights on the front of the dress will move in sync with the music.

[Sahrye] started the dress portion of Conductive Melody with a sketch of the garment’s broad strokes, then painted a more final drawing with lots of detail. Then she made a muslin, which is kind of the breadboard version of a project in garment-making where thin cotton fabric is used to help visualize the end result. Once satisfied with the fit, [Sahrye] then made the final dress out of good fabric. And we mean really good fabric — silk, in this case. Because as [Sahrye] says, if you’re going to make a one-off, why not make as nicely as possible? We can totally get behind that.

[Sahrye] says she is always thinking about how a wearable will be worn, and how it will be washed or otherwise cared for. That sequined and semi-sheer section of the bodice hides the LEDs and their wiring quite well, while still being comfortable for the wearer.

Inside the sleeve is an MPRP121 capacitive touch sensor and an Arduino that controls the LEDs and sends the signals to a Raspberry Pi hidden among the ruffles in the back of the dress.

The Pi is running Piano Genie, which can turn eight inputs into an 88-key piano in real time. When no one is playing the sleeve, the lights have a standby mode of mellow yellows and whites that fade in and out slowly compared to the more upbeat rainbow of musical mode.

We love to see wearable projects — especially such fancy creations! — but we know how finicky they can be. Among the lessons learned by [Sahrye] and [Hal]: don’t make your conductive fabric traces too thin, and silver conductive materials may tarnish irreparably. We just hope they didn’t have to waste too much conductive fabric or that nice blue silk to find this out.

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.

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.

When a new board drops, makers around the planet immediately start hacking new projects with it. Here are 17 fun projects to try on fresh hardware.

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Dev boards give makers limitless options for their projects. Some of our high-tech pals share their personal processes to pick a board.

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Mind control might seem like something out of a sci-fi show, but like the tablet computer, universal translator, or virtual reality device, is actually a technology that has made it into the real world. While these devices often requires on advanced and expensive equipment to interpret brain waves properly, with the right machine learning system it’s possible to do things like this mind-controlled flame thrower on a much smaller budget. (Video, embedded below.)

[Nathaniel F] was already experimenting with using brain-computer interfaces and machine learning, and wanted to see if he could build something practical combining these two technologies. Instead of turning to an EEG machine to read brain patterns, he picked up a much less expensive Mindflex and paired it with a machine learning system running TensorFlow to make up for some of its shortcomings. The processing is done by a Raspberry Pi 4, which sends commands to an Arduino to fire the flamethrower when it detects the proper thought patterns. Don’t forget the flamethrower part of this build either: it was designed and built entirely by [Nathanial F] as well using gas and an arc lighter.

While the build took many hours of training to gather the proper amount of data to build the neural network and works as the proof of concept he was hoping for, [Nathaniel F] notes that it could be improved by replacing the outdated Mindflex with a better EEG. For now though, we appreciate seeing sci-fi in the real world in projects like this, or in other mind-controlled projects like this one which converts a prosthetic arm into a mind-controlled music synthesizer.