Instructables user [Osprey22] has been building towards this Christmas for years. Why? This year, he has brought an impressive musical Christmas light display inside, and at a fraction of the cost too!
An box at the tree’s base hides the power supply and the controller boards — a Raspberry Pi and a SanDevices e682 Pixel controller for the 400 WS2811 RGB LEDs — with an added router to connect them to the main network. The Pi is running Falcon Pi Player and a projector somewhere in the region of $100 complements the light show.
As far as mapping out the LEDs, Xlights is the program of choice, locating the LEDs in space with the help of a cell phone video recording. [Osprey22] had to write a quick program in C to fix the LED overlaps in the grid. (A spreadsheet would work just as well, here). Oh, and the gifts at the bottom of the tree double as a projector screen!
For this year’s office holiday party, [Gavan Fantom] wanted to do something really special. Coworkers were messing with LEDs to come up with displays and decorations, but they lack that old-school feel of mechanical displays. He wanted to create something that had retro look of moving elements, but didn’t want to just recreate the traditional flip mechanism we’ve all seen over and over.
The mechanism to drive a single “pixel”.
What [Gavan] came up with is breathtakingly impractical 8×8 display that sounds as cool as it looks. Each “pixel” in the display is a 3D printed screw mechanism rotated by a hobby servo. As the pixel is rotated in its case, it becomes progressively more visible to the observer. The opacity of the pixel can even be adjusted by varying the degree of rotation, allowing for rudimentary display of grayscale images.
Each element in the display is made up of seven 3D printed parts and two nails, which the mechanism slides on to move forward and backward. An 8×8 display needs 64 elements, which means the entire display needs 64 servos, 128 nails, and a whopping 448 3D-printed parts. Even with two printers attacking the production in parallel, the printing alone took over two weeks to complete.
The display is powered by a Raspberry Pi and three “Mini Maestro” controllers which can each handle 24 servos. [Gavan] found some sample code in Python to pass commands to the Maestro servo controllers, which he used as a template when writing his own software. The Python script opens image files, converts them to grayscale, and then maps the value of each pixel to rotation of the corresponding servo. He says the software is a little rough and that there’s still some calibration to be done, but we think the results are phenomenal so far.
Google has announced their soon to be available Vision Kit, their next easy to assemble Artificial Intelligence Yourself (AIY) product. You’ll have to provide your own Raspberry Pi Zero W but that’s okay since what makes this special is Google’s VisionBonnet board that they do provide, basically a low power neural network accelerator board running TensorFlow.
AIY VisionBonnet with Myriad 2 (MA2450) chip
The VisionBonnet is built around the Intel® Movidius™ Myriad 2 (aka MA2450) vision processing unit (VPU) chip. See the video below for an overview of this chip, but what it allows is the rapid processing of compute-intensive neural networks. We don’t think you’d use it for training the neural nets, just for doing the inference, or in human terms, for making use of the trained neural nets. It may be worth getting the kit for this board alone to use in your own hacks. An alternative is to get Modivius’s Neural Compute Stick, which has the same chip on a USB stick for around $80, not quite double the Vision Kit’s $45 price tag.
The Vision Kit isn’t out yet so we can’t be certain of the details, but based on the hardware it looks like you’ll point the camera at something, press a button and it will speak. We’ve seen this before with this talking object recognizer on a Pi 3 (full disclosure, it was made by yours truly) but without the hardware acceleration, a single object recognition took around 10 seconds. In the vision kit we expect the recognition will be in real-time. So the Vision Kit may be much more dynamic than that. And in case it wasn’t clear, a key feature is that nothing is done on the cloud here, all processing is local.
The kit comes with three different applications: an object recognition one that can recognize up to 1000 different classes of objects, another that recognizes faces and their expressions, and a third that detects people, cats, and dogs. While you can get up to a lot of mischief with just that, you can run your own neural networks too. If you need a refresher on TensorFlow then check out our introduction. And be sure to check out the Myriad 2 VPU video below the break.
Remember the days when the television was the most important appliance in the house? On at dawn for the morning news and weather, and off when Johnny Carson said goodnight, it was the indispensable portal to the larger world. Broadcast TV may have relinquished its hold on the public mind in favor of smartphones, but an information portal built into an old TV might take you back to the old days.
It seems like [MisterM] has a little bit of a thing for the retro look. Witness the wallpaper in the video after the break for proof, as well as his Google-ized Radio Shack intercom project from a few months back. His current project should fit right in, based on an 8″ black-and-white TV from the 70s as it is. TVs were bulky back then to allow for the long neck of the CRT, so he decided to lop off the majority of the case and use just the bezel for his build. An 8″ Pimoroni display sits where the old tube once lived, and replicates the original 4:3 aspect ratio. With Chromium set up in kiosk mode, the family can quickly select from a variety of news and information “channels” using the original tuning knob, while parts from a salvaged mouse turns the volume control into a scroll wheel.
After a friend bought a nannycam that required the use of a cloud service to make the device useful, [Martin Caarels] thought to himself — as he puts it — ”I can probably do this with a Raspberry Pi!”
Altogether, [Caarels] gathered together a 4000mAh battery, a Raspberry Pi 3 with a micro SD card for storage, a Logitech c270 webcam, and the critical component to bind this project together: an elastic band. Once he had downloaded and set up Raspbian Stretch Lite on the SD card, he popped it into the Pi and connected it to the network via a cable. From there, he had to ssh into the Pi to get its IP so he could have it hop onto the WiFi.
Now that he effectively had a wireless webcam, it was time to turn it into a proper security camera.
For the most part, when we break out the soldering iron to make a project for ourselves – we do so for fun. Sometimes we do so for necessity. Rarely do we, however, do so to save our own lives. [Dana Lewis] is one of the 30 million people in the US who suffer from diabetes. It’s a condition where the pancreas fails to make insulin, resulting in a buildup of sugar in the bloodstream. Managing the levels of insulin and sugar in their bodies is a day-to-day struggle for the millions of diabetics in the world. It’s a great deal more for [Dana], however. She sleeps with machines that monitor the glucose levels in her blood, but lives with constant worry.
“I was afraid at night because I am a super-deep, champion sleeper,” Lewis said, “I sleep through the alarms on the device that are supposed to wake me up and save my life…”
What she needed was the glucose data from the device and use it to trigger a louder alarm. It wasn’t long until she found someone who had done just this. Using a Raspberry Pi, she was able to capture the data and then alarm her via her phone. She then setup a web interface so others could see her data and call her if she didn’t wake.
The next step is obvious. Why not make the state of the insulin pump a function of the data? And thus, a sort of artificial pancreas.
The project is open source for anyone to use and improve upon. She was placed on a list for the 100 most creative people in the US for 2017. We’re not strangers to the idea of an artificial pancreas, but it’s always great to see people using things we make video game consoles out of to save lives.
When somebody tackles an engineering problem, there are two possible paths: they can throw together a quick and dirty fix that fits their needs (the classic “hack”, as it were), or they can go the extra mile to develop a well documented solution that helps the community as a whole. We cover it all here at Hackaday, but we’ve certainly got a soft spot for the latter approach, even if some may feel it falls into the dreaded territory of “Not A Hack”.
Even if you aren’t terribly interested in peering into the infinite void above, the extremely detailed write-up [Gary] has done contains tons of multidisciplinary information that you may find useful. From showing how to modify the Pi’s boot configuration to enable true hardware UART (by default, the Pi 3 ties it up with Bluetooth) and level shifting it with a ST3232 to a breakdown of the mistakes he made in his PCB layout, there’s plenty to learn.
