Reggaeton-Be-Gone Disconnects Obnoxious Bluetooth Speakers

If you’re currently living outside of a Spanish-speaking country, it’s possible you’ve only heard of the music genre Reggaeton in passing, if at all. In places with large Spanish populations, though, it would be more surprising if you hadn’t heard it. It’s so popular especially in the Carribean and Latin America that it’s gotten on the nerves of some, most notably [Roni] whose neighbor might not do anything else but listen to this style of music, which can be heard through the walls. To solve the problem [Roni] is now introducing the Reggaeton-Be-Gone. (Google Translate from Spanish)

Inspired by the TV-B-Gone devices which purported to be able to turn off annoying TVs in bars, restaurants, and other places, this device can listen to music being played in the surrounding area and identify whether or not it is hearing Reggaeton. It does this using machine learning, taking samples of the audio it hears and making decisions based on a trained model. When the software, running on a Raspberry Pi, makes a positive identification of one of these songs, it looks for Bluetooth devices in the area and attempts to communicate with them in a number of ways, hopefully rapidly enough to disrupt their intended connections.

In testing with [Roni]’s neighbor, the device seems to show promise although it doesn’t completely disconnect the speaker from its host, instead only interfering with it enough for the neighbor to change locations. Clearly it merits further testing, and possibly other models trained for people who use Bluetooth speakers when skiing, hiking, or working out. Eventually the code will be posted to this GitHub page, but until then it’s not the only way to interfere with your neighbor’s annoying stereo.

Thanks to [BaldPower] and [Alfredo] for the tips!

Modeling A Guitar For Circuit Simulation

Guitar effects have come a long way from the jangly, unaltered sounds of the 1950s when rock and roll started picking up steam. Starting in large part with [Jimi Hendrix] in the 60s, the number of available effects available to guitarists snowballed in the following decades step-by-step with the burgeoning electronics industry. Now, there are tons of effects, from simple analog devices that would have been familiar to [Hendrix] to complex, far-reaching, digital effects available to anyone with a computer. Another thing available to modern guitarists is the ability to model these effects and guitars in circuit simulators, as [Iain] does.

[Ian] plays a Fender Stratocaster, but in order to build effects pedals and amplifiers for it with the exact desired sound, he needed a way to model its equivalent circuit. For a simple DC circuit, this isn’t too difficult since it just requires measuring the resistance, capacitance, and inductance of the overall circuit and can be done with something as simple as a multimeter. But for something with the wide frequency range of a guitar, a little bit more effort needs to go into creating an accurate model. [Iain] is using an Analog Discovery as a vector network analyzer to get all of the raw data he needs for the model before moving on to some in-depth calculations.

[Iain] takes us through all of the methods of figuring out the equivalent impedance of his guitar and its cabling using simple methods capable of being done largely by hand and more advanced techniques like finding numerical solutions. By analyzing the impedance of the pickup, tone and volume controls, and cable, this deep dive into the complexities of building an accurate equivalent circuit model for his guitar could be replicated by anyone else looking to build effects for their specific guitars. If you’re looking for a more digital solution, though, we’ve seen some impressive effects built using other tools unavailable to guitarists in days of yore, such as MIDI and the Raspberry Pi.

Making A Kid-Scale Apollo 11 Lunar Lander

If you’d like to see what goes into making a 1/3-scale Apollo 11 Lunar Module, [Plasanator]’s photos and build details will show off how he constructed one for a kid’s event that was a hit!

The photo gallery gives plenty of ideas about how one would approach a project like this, and readers will surely appreciate the use of an old frying pan as a concrete mold to create the lander’s “feet”. Later, a little paint makes the frying pan become a pseudo-antenna mounted on the lander’s exterior.

Inside, the lander has a control panel with a lot of arcade-style buttons and LED lighting. It’s pretty simple stuff, but livens things up a lot. Bright red lighting for the engine combined with a couple of slow strobe lights really makes it come alive in the dark. The gold foil? Emergency thermal blankets wrapped around the frame.

We happen to have the perfect chaser for this kid-scale lunar module: the Apollo 11 moon landing, recreated with animatronics and LEGO.

Continue reading “Making A Kid-Scale Apollo 11 Lunar Lander”

3D Design With Text-Based AI

Generative AI is the new thing right now, proving to be a useful tool both for professional programmers, writers of high school essays and all kinds of other applications in between. It’s also been shown to be effective in generating images, as the DALL-E program has demonstrated with its impressive image-creating abilities. It should surprise no one as this type of AI continues to make in-roads into other areas, this time with a program from OpenAI called Shap-E which can render 3D images.

Like most of OpenAI’s offerings, this takes plain language as its input and can generate relatively simple 3D models with this text. The examples given by OpenAI include some bizarre models using text prompts such as a chair shaped like an avocado or an airplane that looks like a banana. It can generate textured meshes and neural radiance fields, both of which have various advantages when it comes to available computing power, training methods, and other considerations. The 3D models that it is able to generate have a Super Nintendo-style feel to them but we can only expect this technology to grow exponentially like other AI has been doing lately.

For those wondering about the name, it’s apparently a play on the 2D rendering program DALL-E which is itself a combination of the names of the famous robot WALL-E and the famous artist Salvador Dali. The Shap-E program is available for anyone to use from this GitHub page. Even though this code comes from OpenAI themselves, plenty are speculating that the AI revolution to come will largely come from open-source sources rather than OpenAI or Google, something for which the future is somewhat hazy.

Holograms Display Time With ESP32

Holograms and holographic imagery are typically viewed within the frame of science fiction, with perhaps the most iconic examples being Princess Leia’s message to Obi-Wan in Star Wars, or the holodecks from Star Trek. In reality, holograms have been around for a surprising amount of time, with early holographic images being produced in the late 1940s. There are plenty of uses outside of imagery for modern holographic systems as well, and it’s a common enough technology that it’s possible to construct one using an ESP32 as well.

In this build, [Fiberpunk] demonstrates the construction and operation of a holographic clock. The image is three-dimensional and somewhat transparent and is driven by an ESP32 microcontroller. The display is based around a beamsplitter prism which, when viewed from the front, is almost completely invisible to the viewer. The ESP32 is housed in a casing beneath this prism, and [Fiberpunk] has two firmware versions available for the device. The first is the clock which displays an image as well as the time, and the second is more of a demonstration which can show more in-depth 3D videos using gcode models and also has motion sensing controls.

For anyone interested in holography, a platform like this is might make an excellent entry point to explore, and with the source for this build available becomes even easier. It’s almost certainly less expensive than these 3D printers that can turn out custom holographic images, and has the added benefit of being customizable and programmable as well.

Continue reading “Holograms Display Time With ESP32”

Smart Bike Suspension Tunes Your Ride On The Fly

Riding a bike is a pretty simple affair, but like with many things, technology marches on and adds complications. Where once all you had to worry about was pumping the cranks and shifting the gears, now a lot of bikes have front suspensions that need to be adjusted for different riding conditions. Great for efficiency and ride comfort, but a little tough to accomplish while you’re underway.

Luckily, there’s a solution to that, in the form of this active suspension system by [Jallson S]. The active bit is a servo, which is attached to the adjustment valve on the top of the front fork of the bike. The servo moves the valve between fully locked, for smooth surfaces, and wide open, for rough terrain. There’s also a stop in between, which partially softens the suspension for moderate terrain. The 9-gram hobby servo rotates the valve with the help of a 3D printed gear train.

But that’s not all. Rather than just letting the rider control the ride stiffness from a handlebar-mounted switch, [Jallson S] added a little intelligence into the mix. Ride data from the accelerometer on an Arduino Nano 33 BLE Sense was captured on a smartphone via Arduino Science Journal. The data was processed through Edge Impulse Studio to create models for five different ride surfaces and rider styles. This allows the stiffness to be optimized for current ride conditions — check it out in action in the video below.

[Jallson S] is quick to point out that this is a prototype, and that niceties like weatherproofing still have to be addressed. But it seems like a solid start — now let’s see it teamed up with an Arduino shifter.

Continue reading “Smart Bike Suspension Tunes Your Ride On The Fly”

Machine Learning Makes Sure Your LOLs Are Genuine

There was a time not too long ago when “LOL” actually meant something online. If someone went through the trouble of putting LOL into an email or text, you could be sure they were actually LOL-ing while they were typing — it was part of the social compact that made the Internet such a wholesome and inviting place. But no more — LOL has been reduced to a mere punctuation mark, with no guarantee that the sender was actually laughing, chuckling, chortling, or even snickering. What have we become?

To put an end to this madness, [Brian Moore] has come up with the LOL verifier. Like darn near every project we see these days, it uses a machine learning algorithm — EdgeImpulse in this case. It detects a laugh by comparing audio input against an exhaustive model of [Brian]’s jocular outbursts — he says it took nearly three full minutes to collect the training set. A Teensy 4.1 takes care of HID duties; if a typed “LOL” correlates to some variety of laugh, the initialism is verified with a time and date stamp. If your LOL was judged insincere – well, that’s on you. See what you think of the short video below — we genuinely LOL’d. And while we’re looking forward to a ROTFL verifier, we’re not sure we want to see his take on LMAO.

Hats off to [Brian] for his attempt to enforce some kind of standards online. You may recall his earlier attempt to make leaving Zoom calls a little less awkward, which we also appreciate.

Continue reading “Machine Learning Makes Sure Your LOLs Are Genuine”