Flip-Dot Display Brought Out Of Retirement By New Drivers

November 21, 2017 by 16 Comments

LED matrix displays and flat-screen monitors have largely supplanted old-school electromechanical models for public signage. We think that’s a shame, but it’s also a boon for the tinkerer, as old displays can be had for a song these days in the online markets.

Such was the case for [John Whittington] and his flip-dot display salvaged from an old bus. He wanted to put the old sign back to work, but without a decent driver, he did what one does in these situations — he tore it down and reverse engineered the thing. Like most such displays, his Hannover Display 7 x 56-pixel flip-dot sign is electromechanically interesting; each pixel is a card straddling the poles of a small electromagnet. Pulse the magnet and the card flips over, changing the pixel from black to fluorescent green. [John] used an existing driver for the sign and a logic analyzer to determine the protocol used by the internal electronics to drive the pixels, and came up with a much-improved method of sending characters and graphics. With a Raspberry Pi and power supply now resident inside the case, a web-based GUI lets him display messages easily. The video below has lots of details, and the code is freely available.

You may recall [John] from a recent edge-lit Nixie-like display. Looks like he’s got a thing for eye-catching displays, and we’re fine with that.

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Anouk Wipprecht: Robotic Dresses And Human Interfaces

November 21, 2017 by 11 Comments

Anouk Wipprecht‘s hackerly interests are hard to summarize, so bear with us. She works primarily on technological dresses, making fashion with themes inspired by nature, but making it interactive. If that sounds a little bit vague, consider that she’s made over 40 pieces of clothing, from a spider dress that attacks when someone enters your personal space too quickly to a suit with plasma balls that lets her get hit by Arc Attack’s giant musical Tesla coils in style. She gave an inspiring talk at the 2017 Hackaday Superconference, embedded below, that you should really go watch.

Anouk has some neat insights about how the world of fashion and technology interact. Technology, and her series of spider dresses in particular, tends to evolve over related versions, while fashion tends to seek the brand-new and the now. Managing these two impulses can’t be easy.

For instance, her first spider was made with servos and laser-cut acrylic, in a construction that probably seems familiar to most Hackaday readers. But hard edges, brittle plastic, and screws that work themselves slowly loose are no match for human-borne designs. Her most recent version is stunningly beautiful, made of 3D printed nylon for flexibility, and really nails the “bones of a human-spider hybrid” aesthetic that she’s going for.

The multiple iterations of her drink-dispensing “cocktail dress” (get it?!) show the same progression. We appreciate the simple, press-button-get-drink version that she designed for a fancy restaurant in Ibiza, but we really love the idea of being a human ice-breaker at parties that another version brings to the mix: to get a drink, you have to play “truth or dare” with questions randomly chosen and displayed on a screen on the wearer’s arm.

Playfulness runs through nearly everything that Anouk creates. She starts out with a “what if?” and runs with it. But she’s not just playing around. She’s also a very dedicated documenter of her projects, because she believes in paying the inspiration forward to the next generation. And her latest project does something really brilliant: merging fashion, technology, and medical diagnostics.

It’s a stripped-down EEG that kids with ADHD can wear around in their daily lives that triggers a camera when their brains get stimulated in particular ways. Instead of a full EEG that requires a child to have 30 gel electrodes installed, and which can only be run in a medical lab, stripping down the system allows the child to go about their normal life. This approach may collect limited data in comparison to the full setup, but since it’s collected under less intimidating circumstances, the little data that it does collect may be more “real”. This project is currently in progress, so we’ll just have to wait and see what comes out. We’re excited.

There’s so much more going on in Anouk’s presentation, but don’t take our word for it. Go watch Anouk’s talk right now and you’ll find she inspires you to adds a little bit more of the human element into your projects. Be playful, awkward, or experimental. But above all, be awesome!

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Joan Feynman Found Her Place In The Sun

November 21, 2017 by 45 Comments

Google ‘Joan Feynman’ and you can feel the search behemoth consider asking for clarification. Did you mean: Richard Feynman? Image search is even more biased toward Richard. After maybe seven pictures of Joan, there’s an endless scroll of Richard alone, Richard playing the bongos, Richard with Arline, the love of his life.

Yes, Joan was overshadowed by her older brother, but what physicist of the era wasn’t? Richard didn’t do it on purpose. In fact, no one supported Joan’s scientific dreams more than he did, not even their mother. Before Richard ever illuminated the world with his brilliance, he shined a light on his little sister, Joan.

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Python Keeps A Gecko Happy: Terrarium Automation With Raspberry Pi

November 21, 2017 by 8 Comments

For better or worse, pets often serve as inspiration and test subjects for hardware hacks: smarten up that hamster wheel, tweet the squirrel hunting adventures from a dog’s point of view, or automate and remote control a reptile enclosure. [TheYOSH], a gecko breeder from the Netherlands, chose the latter and wrote TerrariumPi for the Raspberry Pi to control and monitor his exotic companion’s home through a convenient web interface.

The right ecosystem is crucial to the health and happiness of any animal that isn’t native to its involuntarily chosen surroundings. Simulating temperature, humidity and lighting of its natural habitat should therefore be the number one priority for any pet owner. The more that simulation process is reliably automated, the less anyone needs to worry.

TerrariumPi supports all the common temperature/humidity sensors and relay boards you will find for the Raspberry Pi out of the box, and can utilize heating and cooling, watering and spraying, as well as lighting based on fixed time intervals or sensor feedback. It even supports location based sunrise and sunset simulation — your critter might just think it never left Madagascar, New Caledonia or Brazil. All the configuration and monitoring happens in the browser, as demonstrated in [TheYOSH]’s live system with public read access (in Dutch).

It only seems natural that Python was the language of choice for a reptile-related system. On the other hand, it doesn’t have to be strictly used for reptiles or even terrariums; TerrariumPi will take care of aquariums and any other type of vivarium equally well. After all, we have seen the Raspberry Pi handling greenhouses and automating mushroom cultivation before.

Hackers Vs. Mold: Building A Humidistat Fan

November 21, 2017 by 29 Comments

Having a mold problem in your home is terrible, especially if you have an allergy to it. It can be toxic, aggravate asthma, and damage your possessions. But let’s be honest, before you even get to those listed issues, having mold where you live feels disgusting.

You can clean it with the regular use of unpleasant chemicals like bleach, although only with limited effectiveness. So I was not particularly happy to discover mold growing on the kitchen wall, and decided to do science at it. Happily, I managed to fix my mold problems with a little bit of hacker ingenuity.

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Mad Eye For The WiFi

November 21, 2017 by 12 Comments

In the Harry Potter universe, Professor Moody was, perhaps unfairly, given the nickname Mad Eye for the prosthetic eye he wore. His eye remains a challenge for technically-minded cosplayers aiming to recreate the look and feel of this unique piece of headgear. [cyborgworkshop] had already mastered the basic eye, but wanted to take things further.

The original build relied on a sub-micro servo to move the eyeball. This was done at random as an attempt to simulate the eye’s behaviour in the books and films. However, wanting more, [cyborgworkshop] decided to make the eye more reactive to its surrounding environment. Using the Adafruit Huzzah, a breakout board for the ESP8266, code was whipped up to detect the number of WiFi access points in the area. The more access points, the more frequent and erratic the movement of the eye. Occasional slower periods of movement are coded in before the eye resumes its wild darting once more, depending on just how saturated the local WiFi environment is.

It’s a great twist on the project, and [cyborgworkshop] has provided more details on the initial build, too. If you think you’re having déja vu, check out this build using recycled parts.

Prototyping, Making A Board For, And Coding An ARM Neural Net Robot

November 21, 2017 by 1 Comment

[Sean Hodgins]’s calls his three-part video series an Arduino Neural Network Robot but we’d rather call it an enjoyable series on prototyping, designing a board with surface mount parts, assembling it, and oh yeah, putting a neural network on it, all the while offering plenty of useful tips.

In part one, prototype and design, he starts us out with a prototype using a breadboard. The final robot isn’t on an Arduino, but instead is on a custom-made board built around an ARM Cortex-M0+ processor. However, for the prototype, he uses a SparkFun SAM21 Arduino-sized board, a Pololu DRV8835 dual motor driver board, four photoresistors, two motors, a battery, and sundry other parts.

Once he’s proven the prototype works, he creates the schematic for his custom board. Rather than start from scratch, he goes to SparkFun’s and Pololu’s websites for the schematics of their boards and incorporates those into his design. From there he talks about how and why he starts out in a CAD program, then moves on to KiCad where he talks about his approach to layout.

Part two is about soldering and assembly, from how he sorts the components while still in their shipping packages, to tips on doing the reflow in a toaster oven, and fixing bridges and parts that aren’t on all their pads, including the microprocessor.

In Part three he writes the code. The robot’s objective is simple, run away from the light. He first tests the photoresistors without the motors and then writes a procedural program to make the robot afraid of the light, this time with the motors. Finally, he writes the neural network code, but not before first giving a decent explanation of how the neural network works. He admits that you don’t really need a neural network to make the robot run away from the light. But from his comparisons of the robot running using the procedural approach and then the neural network approach, we think the neural network one responds better to what would be the in-between cases for the procedural approach. Admittedly, it could be that a better procedural version could be written, but having the neural network saved him the trouble and he’s shown us a lot that can be reused from the effort.

In case you want to replicate this, [Sean]’s provided a GitHub page with BOM, code and so on. Check out all three parts below, or watch just the parts that interest you.

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