The Raspberry Pi Cluster From Outer Space

We see a lot of weird and esoteric stuff here at Hackaday, but even by our standards, Bell Lab’s Plan 9 operating system is an oddball. Named after the science fiction film Plan 9 from Outer Space, it was designed to extend the UNIX “everything is a file” mentality to the network. It envisioned a future where utilizing the resources of another computer would be as easy as copying a file. But as desktop computers got more powerful the idea seemed less appealing, and ultimately traditional operating systems won out. Of course, that doesn’t mean you still can’t play around with it.

Logically to make use of a distributed operating system you really need something to distribute it on, but as [Andrew Back] shows, today that’s not nearly the challenge it would have been back then. Using the Raspberry Pi, he builds a four-node Plan 9 cluster that’s not only an excellent way to explore this experimental operating system, but looks cool sitting on your desk. Even if you’re not interested in drinking the Bell Lab’s Kool-Aid circa 1992, his slick desktop cluster design would work just as well for getting your feet wet with modern-day distributed software stacks.

The enclosure for the cluster is built from laser cut acrylic panels which are then folded into shape with a hot wire bending machine. That might seem like a tall order for the home hacker, but we’ve covered DIY acrylic benders in the past, and the process is surprisingly simple. Granted you’ll still need to get access to a beefy laser cutter, but that’s not too hard anymore if you’ve got a hackerspace nearby.

[Andrew] uses short extension cables and female panel mount connectors to keep everything tidy, and with the addition of some internal LED lighting the final product really does look like a desktop computer from a far more fashionable future. Combined with the minimalist keyboard, the whole setup wouldn’t look out of place on the set of a science fiction movie. Perhaps that’s fitting, giving Bell Lab’s futuristic goals for Plan 9.

Its been the better part of a decade since we first brought you word that Plan 9 was available for the Raspberry Pi, and yet in all that time we’ve never really seen it put to use. Hopefully builds like this will inspire others to play around with this fascinating piece of computing history.

[Thanks to Dave for the tip.]

This Raspberry Pi Is NASty

A piratebox is a small computer, WiFi adapter, and a hard drive. The idea behind the piratebox is to simply put some storage on a network, accessible to all. It’s great if you’re in a group, need an easy way to share files at the hackerspace, or just want to put a modern twist on a LAN party. [Nick] and [Josiah] came up with their own twist on a piratebox, and this one uses a Raspberry Pi Zero W, making it one of the cheapest pirateboxes around.

The Raspberry Pi Zero W, with its network adapter, has all the hardware required to turn into a capable piratebox, so the hardware for this build is pretty simple. It’s just a USB A plug in the form of a USB Stem and nothing else. The software is available on GitHub and broadcasts a WiFi network named SUBZero. Browsing to 192.168.1.1 on this network allows for uploading and downloading files, all without an Internet connection. It’s a cloud that will fit in your pocket, which we’re calling a ‘fog’ or a ‘mist’ this week. Since this is called the ‘SUBZero’, perhaps ‘pogonip’ is the preferred nomenclature.

Of course no Raspberry Pi project is complete without a 3D printed case, and the SUBZero is no exception. There’s a 3D printed case for this Pi Zero, complete with a sliding door for access to all the ports. You can see a video of that below.

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Raspberry Pi Camera With Smarts — Cloud Or Local?

[Mark West] gave an interesting presentation at last year’s GOTO Copenhagen conference. He shows how he took a simple Raspberry Pi Zero webcam and expanded it with AI. He actually added the intelligent features in two different ways: on in the Amazon cloud and another using the Intel Modvidius NCS USB stick directly connected to the USB. You can see the video below.

Local motion detection uses some open source software. You simply configure it using a text file and it even handles the video streaming. However, at that point, you just have a web camera — not amazing, nor very cost effective. However, you get a lot of false alarms with the motion detection software. A random cat walking past, clouds, trees, or even rain would push [Mark] an email and after 250 alert e-mails a day, [Mark] decided to make something better.

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Fueled By Jealousy, This Smart Lamp Really Shines

As a lover of lava lamps, [Julian Butler] knew when he saw a coworker’s modern LED incarnation of the classic piece of illuminated decor that he had to have one for himself. The only problem was that the Kickstarter for it had long since ended, and they were no longer available. So he did what any good hacker would do: he studied it closely, took a bunch of notes, and built his own version that ended up being even better than the original.

In the three part series on his blog, [Julian] takes us through the design and construction of his take on the Ion Mood Light, which raised over $72,000 back in 2014. The details in the Kickstarter campaign plus his own first-hand observations of the device were enough to give him the high-level summary: the device has a core of RGB LEDs behind a diffuser, and uses some software trickery to pulse out some pleasing effects and patterns. He wasn’t concerned about the Bluetooth or the smartphone application, so all he really needed to do was put some NeoPixel LEDs inside a glass cylinder and he’d be done. Of course, it always sounds easy…

The actual journey to get there, as you might have guessed from the three part series, took awhile. Sourcing the LEDs was easy enough, and using a Fadecandy controller made getting the LEDs to blink out some cool patterns fairly straightforward. But it took [Julian] a bit of experimentation and a few trips to the crafts store before he found a material which would diffuse the LEDs enough for his tastes. Though in the end, he thinks the multiple layers of acrylic he ended up going with actually do a better job of blending the light from the individual LEDs than in the original Ion.

Using the Fadecandy made it easy to drive the LEDs, but he still needed something to provide it with the commands. To that end, he added a decorative base to his LED column that hides a Raspberry Pi and all the lamp’s associated electronics. This includes a microphone which gives his lamp the same sort of sound reactive features that made the Ion so popular. The base does make his lamp a bit bulkier than the original version, but the metallic mesh construction is attractive enough the overall look works.

Of course, you might be wondering how [Julian] got the LEDs to react to sound, or do any of the other gorgeous effects shown off in the video after the break. The software which makes this possible makes up the third and final post in the series, and is really a whole project in itself. The short version of the story is that he used Python and Processing to do real-time computational fluid dynamics, but not before making the necessary adjustments to speed up the simulation on ARM hardware. You know, normal lamp stuff.

This isn’t the first time we’ve seen projects using the Fadecandy board. From creating a Tron inspired desk to building the 5,760 LED “Space Tunnel”, it looks like a great choice if you’ve got a problem that can be solved by the application of a ridiculous number of LEDS.

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Balena Introduces DIN-Capable Pi Compute Module Carrier Board

Although you don’t hear about it very much over the clamor of emulating old video game systems, one of the biggest uses of the Raspberry Pi outside its educational roots is in industry. The Pi makes for a great industrial control system, and if you mount it to a DIN rail, you’re golden. This is the biggest reason the Pi foundation is still making the Pi 1, and it’s one of the big motivations behind the Pi Compute Module.

Now that the Pi Compute Module 3 and 3+ have been out for a while, it’s only fitting that these modules get a great carrier board. The balenaFin 1.1 is out now, and it’s the perfect carrier board for the Pi compute module.

Balena (formerly resin.io) is a software stack designed for managing fleets of Linux devices, and there’s no better example of that than a factory filled with Pis fiddling relays and such. Balena has found its way from tracking sea turtles to monitoring oil rigs, and with that comes a need for a developer kit. The Pi compute module is supposed to have a very long support life, so the obvious solution is to make a great carrier board for this fantastic module.

Features of note include two camera connectors, PoE (with a Hat), USB headers, an RGB indicator LED, an industrial temperature range, and a case designed for a DIN rail. So far, so goo, but there’s also a microcontroller with a Bluetooth radio that can operate without the compute module being turned on, and an RTC for time-based operation. There’s a mini PCI express slot designed for cellular modems, and a SIM card slot just for fun.

While most Pi builds we see could make use of these features, they are assuredly one-off builds. You’re not going to be deploying hundreds of Pis if you need to 3D print an enclosure for each one. That’s when actual engineers need to get involved, and if you’re doing that, you might as well go with the Raspberry Pi compute module. If you’re looking for a fleet of Pis, you could do worse than to look at this very nice compute module carrier board.

Leigh Johnson’s Guide To Machine Vision On Raspberry Pi

We salute hackers who make technology useful for people in emerging markets. Leigh Johnson joined that select group when she accepted the challenge to build portable machine vision units that work offline and can be deployed for under $100 each. For hardware, a Raspberry Pi with camera plus screen can fit under that cost ceiling, and the software to give it sight is the focus of her 2018 Hackaday Superconference presentation. (Video also embedded below.)

The talk is a very concise 13 minutes, so Leigh flies through definitions of basic terms, before quickly naming TensorFlow and Keras as the tools she used. The time she saved here was spent on explaining what convolutional neural networks are and how they work, just enough to prepare the audience. But all of that is really just background, the meat of the talk is self-contained examples that Leigh has put together and made available online. I love to see that since it means you go beyond just watching and try it out for yourself. Continue reading “Leigh Johnson’s Guide To Machine Vision On Raspberry Pi”

The Easiest Thermal Camera Build You’ll Ever See

Thermal cameras are one of those tools that we all want, but just can’t justify actually buying. You don’t really know what you would do with one, and when even the cheap ones are a couple hundred dollars, it’s a bit out of the impulse buy territory. So you just keeping waiting and hoping that eventually they’ll drop to the price that you can actually own one yourself.

Well, today might be the day you were waiting for. While it might not be the prettiest build, we think you’ll agree it can’t get much easier than what [vvkuryshev] has put together. His build only has two components: a Raspberry Pi and a thermal camera module he picked up online for about $80 USD. There isn’t even any wiring involved, the camera fits right on the Pi’s GPIO header.

Of course, you probably wouldn’t be seeing this on Hackaday if all he had to do was just buy a module and solder it to the Pi’s header. As with most cheap imported gadgets, the GY-MCU90640 module that [vvkuryshev] bought came with some crusty Windows software which wasn’t going to do him much good on the Raspberry Pi. But after going back and forth a bit with the seller, he was able to get some documentation for the device that put him on the right track to writing a Python script which got it working under Linux.

The surprisingly simple Python script reads a frame from the camera four times a second over serial and run it through OpenCV. It even adds some useful data like the minimum and maximum temperatures in the frame to the top of the image. Normally the script would output to the Pi’s primary display, but if you want to use it remotely, [vvkuryshev] says he’s had pretty good luck running it over VNC. In fact, he says that with a VNC application on your phone you could even use this setup on the go, though the setup is a bit awkward for that in its current incarnation.

This isn’t the first DIY thermal camera build we’ve seen, and it isn’t even the first one we’ve seen that leveraged a commercially available imaging module. But short of buying a turn-key camera, we don’t see how it could get any easier to add heat vision to your bag of tricks.