Quick, what’s the price of Bitcoin? Is it lower today than yesterday? Are you overdrafting your Lamborghini account? What if you had an easy way to tell at a glance how much you could have made if you sold in December of last year? That’s what this Bitcoin price tracking traffic light is all about, and it’s a great use of existing electronics.
The hardware for this build is a traffic light table lamp available on Amazon for twenty bucks. Inside this traffic light, you get a PCB with three LEDs and a small microcontroller to control the LEDs. The microcontroller isn’t used in this case, instead the microcontroller is removed and a few wires are soldered up to the base of the transistors used to drive the LEDs. The other ends of these wires are attached to a trio of pins on a Raspberry Pi Zero W, giving this traffic light table lamp Linux and a connection to the Internet.
On the software side of things, we’re looking at a Docker container running a Python script that fetches the latest Bitcoin price from Coindesk and calculates the change from the previous fetch of the price of Bitcoin. This data is shuffled off to another Python script that actually changes the LEDs on the lamp.
Sure, these days a ‘bitcoin price tracking traffic light’ is as simple as connecting a red LED to a battery, and if you’re feeling extra fancy you can add a 220 Ω resistor. But this is a project that’s so well executed that we’ve got to give it a tip ‘o our hat.
Now that most of what we do revolves around our phones and/or the internet, it’s nearly impossible to take a short break from work to check the ol’ calendar without being lured by the sirens on the shore of social media. Well, [samvanhook] was tired of being drawn in when all he really needs is a vague idea of what’s coming up for him in the next 12 hours. Enter the CalClock.
Thanks to color-coded segments, [sam] can tell at a glance if he has something coming up soon in Google Calendar, or if he can dive back into work. When nothing is scheduled, the segments are simply unlit.
We love the mid-century minimal look and craftsmanship of CalClock. This beauty runs on a Raspi Zero W, which fetches the 411 through the gooCal API and lights up the appropriate NeoPixels arrayed behind standard clock movement-driven hands. [sam] could have diffused the NeoPixels with a single sheet of acrylic, but he went the extra mile to route and sand little acrylic ice cubes for all 24 segments.
[Fatjedi007] recently acquired three programmable boxing gym-type clocks to help his developmentally disabled clients manage their time. The plan was to have timers of varying lengths fire at preset times throughout the day, with the large displays providing a view from anywhere. Unfortunately, the clocks were not nearly as programmable as he needed them to be.
Since he’d spent enough money already, [Fatjedi007] turned to the power of Raspberry Pi to devise an affordable solution. Each clock gets a Pi Zero W and a simple IR transmit/receive circuit that operates using LIRC. The clocks came with remote controls, so it was just a matter of re-programming them. From LIRC, he wrote some scripts with SEND_ONCE and schedules the timers with a cron job. No need to get out the ladder—he can program all of them from his chair over VNC.
He does have one problem, though, and that’s getting the Zeros to set themselves over NTP with static IPs. Do you have any suggestions? Put ’em in the comments and help a Jedi out.
LIRC is pretty handy for anything you want to control remotely, like a stereo system.
You might remember a time when people thought portable DVD players were a pretty neat idea. In the days before netbooks, cheap tablets, and arguably even the widespread adoption of smartphones, it seemed perfectly reasonable to lug around a device that did nothing but play movies. Today we look back at them as we would flip phones: a quaint precursor to the technology overload we find ourselves in currently. But the fact remains that millions of these comical little devices were pumped into the greedy maw of the consumer electronics market. They’re ripe for the hacking, all you need is some inspiration.
So if this grafting of a portable DVD player and the Raspberry Pi Zero W created by [nutsacrilege] doesn’t get you sniffing around your local second-hand store for a donor device, nothing will. By integrating a Pi running Kodi, the player gets a multi-media kick in the pants that arguably makes up for the rather archaic form factor. Not only can it play a wide array of local and online content, but it could even be used as portable game system if you were so inclined.
Rest assured, this isn’t some lazy five-minute mod. All of the original physical controls have been made functional by way of a MCP3008 ADC connected to the Pi’s GPIO and some clever Python scripting. Even the headphone jack was made functional by wiring it up to a USB sound card, and by integrating a tiny stripped down hub he was also able to add an external USB port. Who needs discs when you can plug in a flash drive full of content?
Speaking of which, [nutsacrilege] reports that the original functions of the device are still intact after all his modifications. So if you can get the museum to loan you one, you can even play a DVD on the thing as its creators intended.
Representing the weather on an LED lamp in a manner that’s easy to interpret can be difficult, but [Gosse Adema]’s weather/matrix lamp makes it not only obvious what the weather is but also offers a very attractive display. For rain, drops of light move downward, and for wind, sideways. The temperature is shown using a range of colors from red to blue, and since he is situated in the Netherlands he needed snow, which he shows as white. A rainy, windy day has lights moving both down and sideways with temperature information as the background.
To implement it he mounted LED strips inside a 3D printed cylinder with reflectors for each LED, all of which fitted into a glass cylinder taken from another lamp purchased online. The brains of it is a Raspberry Pi Zero W housed in the bottom along with a fan. Both the LEDs and the fan are controlled by the Pi. He took a lot of care with power management, first calculating the current that the LEDs would draw, and then writing Python code to limit that draw. However upon measurement, the current draw was much lower than expected and so he resized the power supply appropriately. He also took care to correctly size the wires and properly distribute the power with a specially made power distribution board. Overall, we really like the thorough job he’s done.
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.
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.
Usually at Hackaday we like to post projects that are of interest because of their complexity. That’s especially true for robots — the more motors and sensors the better. But, occasionally we come across a project that’s beautiful because of its simplicity. That’s the case with [Max.K’s] ZeroBot, recently posted over on Hackaday.io.