A colorful diagram representing the inner structure of the Linux kernel.

Find That Obscure Function With This Interactive Map Of The Linux Kernel

Linux has become one of the largest operating systems on the servers that run large websites, and hopefully, one day, it will be big in the desktop market too. Some of you may know how Linux as an operating system is structured, but have you ever wondered how the kernel itself is structured? Maybe you’ll find this colorful interactive map of the Linux kernel by [Costa Shulyupin] useful.

The interactive map depicts the major levels of abstraction and functionalities, dotted with over 400 prominent functions from the Linux kernel, which are also links to a cross-reference site so you can see all the definitions and usages. It divides the kernel into 7 rows and 7 columns containing domains with well-known terms like security and debugging, but also more obscure things like block devices and address families. These are also links, this time to the definition of the term in question. Finally, there are arrows flying everywhere, to show the relationships between all the many functions in the kernel.
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Build A Circuit Sculpture-Style VU Meter For Music

One of the coolest things any sound system can have is some kind of musical visualization. Thumping level meters that pump with the volume are a great example, and were particularly popular in the 1980s. Now, you can build a rainbow set with great response, thanks to this guide from [Invexlab World].

The build relies on a very simple circuit that relies entirely on analog electronics in lieu of the usual digital signal analysis usually employed for the job. It’s a barebones design that’s assembled using a jig to create the attractive circuit sculpture structure. It uses simple colored LEDs, assembled in a line with red at the bottom, stepping through yellow and green, to blue and white at the top. A series of diodes is placed in series, with the sound level having to exceed the voltage drop of successive diodes to light the higher LEDs. It’s intended to be directly connected to a speaker’s audio input, and thus likely does load down the amplifier output slightly.

The result is an attractive rainbow VU meter display that would look great as a part of any old-school stereo setup. We can imagine it would look even better if it was cast in clear resin. Video after the break.

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wifi scanner

Visualizing WiFi With A Converted 3D Printer

We all know we live in a soup of electromagnetic radiation, everything from AM radio broadcasts to cosmic rays. Some of it is useful, some is a nuisance, but all of it is invisible. We know it’s there, but we have no idea what the fields look like. Unless you put something like this 3D WiFi field strength visualizer to work, of course.

Granted, based as it is on the gantry of an old 3D printer, [Neumi]’s WiFi scanner has a somewhat limited work envelope. A NodeMCU ESP32 module rides where the printer’s extruder normally resides, and scans through a series of points one centimeter apart. A received signal strength indicator (RSSI) reading is taken from the NodeMCU’s WiFi at each point, and the position and RSSI data for each point are saved to a CSV file. A couple of Python programs then digest the raw data to produce both 2D and 3D scans. The 3D scans are the most revealing — you can actually see a 12.5-cm spacing of signal strength, which corresponds to the wavelength of 2.4-GHz WiFi. The video below shows the data capture process and some of the visualizations.

While it’s still pretty cool at this scale, we’d love to see this scaled up. [Neumi] has already done a large-scale 3D visualization project, using ultrasound rather than radio waves, so he’s had some experience in this area. But perhaps a cable bot or something similar would work for a room-sized experiment. A nice touch would be using an SDR dongle to collect signal strength data, too — it would allow you to look at different parts of the spectrum.

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Ferrofluid Dances In Custom Bluetooth Speaker

Ferrofluids, as the name implies, are liquids that respond to magnetic fields. They were originally developed for use by NASA as rocket fuel but are available to the general public now for anyone who wants to enjoy their unique properties. For [Dakd Jung], that meant building a special chamber into a Bluetooth speaker that causes the ferrofluid inside to dance along with the rhythm of the music.

This project isn’t quite as simple as pushing the ferrofluid container against a speaker, though. A special electromagnetic device similar to a speaker was used specifically to manipulate the fluid, using a MSGEQ7 equalizer to provide the device with only a specific range of frequencies best tailored for the fluid’s movement. The project includes two speakers for playing the actual music that point upward, and everything is housed inside of a 3D-printed case. There were some additional hurdles to overcome as well, like learning that the glass needed a special treatment to keep the ferrofluid from sticking to it.

All in all it’s a unique project that not only brings sound to a room but a pleasing physical visualization as well. Being able to listen to music or podcasts on a portable speaker, rather than the tinny internal speakers of a phone or laptop, is the sort of thing you think you can live without until you get used to having higher quality sound easily and in every place you go. And, if there’s a way to improve on that small but crucial foundation with something like a dancing ferrofluid that moves with the music the speaker is playing, then we’re going to embrace that as well.

Watch Earthquake Roll Across A Continent In Seismograph Visualization Video

If your only exposure to seismologists at work is through film and television, you can be forgiven for thinking they still lay out rolls of paper to examine lines of ink under a magnifying glass. The reality is far more interesting in a field that has eagerly adopted all available technology. A dramatic demonstration of modern earthquake data gathering, processing, and visualization was Tweeted by @IRIS_EPO following a central California quake on July 4th, 2019. In this video can see the quake’s energy propagate across the continental United States in multiple waves of varying speed and intensity. The video is embedded below, but click through to the Twitter thread too as it has a lot more explanation.

The acronym IRIS EPO expands out to Incorporated Research Institutions for Seismology, Education and Public Outreach. We agree with their publicity mission; more people need to know how cool modern seismology is. By combining information from thousands of seismometers, we could see forces that we could not see from any individual location. IRIS makes seismic data available to researchers (or curious data science hackers) in a vast historical database or a real time data stream. Data compilations are presented in several different forms, this particular video is a GMV or Ground Motion Visualization. Significant events like the 4th of July earthquake get their own GMV page where we can see additional details, like the fact this visualization compiled data from 2,132 stations.

If this stirred up interest in seismology, you can join in the fun of networked seismic data. A simple seismograph can be built from quite humble components, but of course there are specially designed chips for the task as well.

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Visual Magnetic Fields

If you need help visualizing magnetic fields, these slow-motion video captures should educate or captivate you. Flux lines are difficult to describe in words, because magnet shape and strength play a part. It might thus be difficult to visualize what is happening with a conical magnet, for a person used to a bar magnet. We should advise you before you watch the video below the break, if you are repelled by the sight of magnetite sand clogging a bare magnet then flying on the floor, this is your only warning.

The technique and equipment are simple and shown in the video. A layer of black sand is spread on a piece of tense plastic to make something like a dirty trampoline, and a neodymium magnet is dropped in the middle. The bouncing action launches the sand and magnet simultaneously so they are hanging in the air and the particles can move with little more than air resistance.

These videos were all taken with a single camera and a single magnet. Multiple cameras would yield 3D visuals, and the intertwining fields of multiple magnets can be beautiful. Perhaps a helix of spherical magnets? What do you have lying around the hosue? In a twist, we can use magnets to simulate gas atoms and trick them into performing unusual feats.

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Making Pictures Worth 1000 Words In Python

In a previous post, I showed how you could upload images into a Discord server from Python; leveraging the popular chat platform to simplify things like remote monitoring and push notifications on mobile devices. As an example, I showed an automatically generated image containing the statistics for my Battlefield 1 platoon which gets pushed to member’s devices on a weekly basis.

Automatically generated stats posted to Discord

The generation of that image was outside the scope of the original post, but I think it’s a technique worth discussing on its own. After all, they say that a picture is worth 1000 words. So that means a picture that actually contains words must be worth way more. Like, at least 2000, easy.

Being able to create images from your textual data can lend a bit of flair to your projects without the need to create an entire graphical user interface. By putting a text overlay on a pre-rendered image, you can pull off some very slick visuals with a minimum amount of system resources. So long as you have a way of displaying an image file, you’re good to go.

In this post I’ll quickly demonstrate how to load an image, overlay it with text, and then save the resulting image to a new file. This technique is ideal in situations where a display doesn’t need to be updated in real-time; visuals can be generated at regular intervals and simply displayed as static images. Possible uses include weather displays, “magic” mirrors, public signage, etc. Continue reading “Making Pictures Worth 1000 Words In Python”