Voice Controlled RGB LEDs Go Big

October 2, 2020 by Tom Nardi 1 Comment

When we see RGB LEDs used in a project, they’re often used more for aesthetic purposes than as a practical source of light. It’s an easy way to throw some color around, but certainly not the sort of thing you’d try to light up anything larger than a desk with. Apparently nobody explained the rules to [Brian Harms] before he built Light[s]well.

Believe it or not, this supersized light installation doesn’t use any exotic hardware you aren’t already familiar with. Fundamentally, what we’re looking at is a WiFi enabled Arduino MKR1000 driving strips of NeoPixel LEDs. It’s just on a far larger scale than we’re used to, with a massive 4 x 8 aluminum extrusion frame suspended over the living room.

Onto that frame, [Brian] has mounted an undulating diffuser made of 74 pieces of laser-cut cardstock. Invoking ideas of waves or clouds, the light looks like its of natural or even biological origin while at the same time having a distinctively otherworldly quality to it.

The effect is even more pronounced when the RGB LEDs kick in, thanks to the smooth transitions between colors. In the video after the break, you can see Light[s]well work its way from bright white to an animated rainbow. As an added touch, he added Alexa voice control through Arduino’s IoT Cloud service.

While LED home lighting is increasingly becoming the norm, projects like Light[s]well remind us that we aren’t really embracing the possibilities offered by the technology. The industry has tried so hard to make LEDs fit into the traditional role of incandescent bulbs, but perhaps its time to rethink things.

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Quadcopter With Stereo Vision

June 30, 2020 by Bryan Cockfield 5 Comments

Flying a quadcopter or other drone can be pretty exciting, especially when using the video signal to do the flying. It’s almost like a real-life video game or flight simulator in a way, except the aircraft is physically real. To bring this experience even closer to the reality of flying, [Kevin] implemented stereo vision on his quadcopter which also adds an impressive amount of functionality to his drone.

While he doesn’t use this particular setup for drone racing or virtual reality, there are some other interesting things that [Kevin] is able to do with it. The cameras, both ESP32 camera modules, can make use of their combined stereo vision capability to determine distances to objects. By leveraging cloud computing services from Amazon to offload some of the processing demands, the quadcopter is able to recognize faces and keep the drone flying at a fixed distance from that face without needing power-hungry computing onboard.

There are a lot of other abilities that this drone unlocks by offloading its resource-hungry tasks to the cloud. It can be flown by using a smartphone or tablet, and has its own web client where its user can observe the facial recognition being performed. Presumably it wouldn’t be too difficult to use this drone for other tasks where having stereoscopic vision is a requirement.

Thanks to [Ilya Mikhelson], a professor at Northwestern University, for this tip about a student’s project.

Free Cloud Data Logging Courtesy Of Google

May 11, 2020 by Tom Nardi 22 Comments

Pushing all of your data into “The Cloud” sounds great, until you remember that what you’re really talking about is somebody else’s computer. That means all your hard-crunched data could potentially become inaccessible should the company running the service go under or change the rules on you; a situation we’ve unfortunately already seen play out.

Which makes this project from [Zoltan Doczi] and [Róbert Szalóki] so appealing. Not only does it show how easy it can be to shuffle your data through the tubes and off to that big data center in the sky, but they send it to one of the few companies that seem incapable of losing market share: Google. But fear not, this isn’t some experimental sensor API that the Big G will decide it’s shutting down next Tuesday in favor of a nearly identical service with a different name. All your precious bits and bytes will be stored in one of Google’s flagship products: Sheets.

It turns out that Sheets has a “Deploy as Web App” function that will spit out a custom URL that clients can use to access the spreadsheet data. This project shows how that feature can be exploited with the help of a little Python code to push data directly into Google’s servers from the Raspberry Pi or other suitably diminutive computer.

Here they’re using a temperature and humidity sensor, but the only limitation is your imagination. As an added bonus, the chart and graph functions in Sheets can be used to make high-quality visualizations of your recorded data at no extra charge.

You might be wondering what would happen if a bunch of hackers all over the world started pushing data into Sheets every few seconds. Honestly, we don’t know. The last time we showed how you could interact with one of their services in unexpected ways, Google announced they were retiring it on the very same day. It was probably just a coincidence, but to be on the safe side, we’d recommend keeping the update frequency fairly low.

Back in 2012, before the service was even known as Google Sheets, we covered how you could do something very similar by manually assembling HTTP packets containing your data. We’d say this validates the concept for long-term data storage, but clearly the methodology has changed considerably in the intervening years. Somebody else’s computer, indeed.

Train All The Things Contest Update

March 3, 2020 by Dan Maloney 2 Comments

Back in January when we announced the Train All the Things contest, we weren’t sure what kind of entries we’d see. Machine learning is a huge and rapidly evolving field, after all, and the traditional barriers that computationally intensive processes face have been falling just as rapidly. Constraints are fading away, and we want you to explore this wild new world and show us what you come up with.

Where Do You Run Your Algorithms?

To give your effort a little structure, we’ve come up with four broad categories:

Machine Learning on the Edge
- Edge computing, where systems reach out to cloud resources but run locally, is all the rage. It allows you to leverage the power of ~~other people’s computers~~ the cloud for training a model, which is then executed locally. Edge computing is a great way to keep your data local.
Machine Learning on the Gateway
- Pi’s, old routers, what-have-yous – we’ve all got a bunch of devices laying around that bridge space between your local world and the cloud. What can you come up with that takes advantage of this unique computing environment?
Machine Learning in the Cloud
- Forget about subtle — this category unleashes the power of the cloud for your application. Whether it’s Google, Azure, or AWS, show us what you can do with all that raw horsepower at your disposal.
Artificial Intelligence Blinky
- Everyone’s “hardware ‘Hello, world'” is blinking an LED, and this is the machine learning version of that. We want you to use a simple microprocessor to run a machine learning algorithm. Amaze us with what you can make an Arduino do.

These Hackers Trained Their Projects, You Should Too!

We’re a little more than a month into the contest. We’ve seen some interesting entries bit of course we’re hungry for more! Here are a few that have caught our eye so far:

Intelligent Bat Detector – [Tegwyn☠Twmffat] has bats in his… backyard, so he built this Jetson Nano-powered device to capture their calls and classify them by species. It’s a fascinating adventure at the intersection of biology and machine learning.
Blackjack Robot – RAIN MAN 2.0 is [Evan Juras]’ cure for the casino adage of “The house always wins.” We wouldn’t try taking the Raspberry Pi card counter to Vegas, but it’s a great example of what YOLO can do.
AI-enabled Glasses – AI meets AR in ShAIdes, [Nick Bild]’s sunglasses equipped with a camera and Nano to provide a user interface to the world. Wave your hand over a lamp and it turns off. Brilliant!

You’ve got till noon Pacific time on April 7, 2020 to get your entry in, and four winners from each of the four categories will be awarded a $100 Tindie gift card, courtesy of our sponsor Digi-Key. It’s time to ramp up your machine learning efforts and get a project entered! We’d love to see more examples of straight cloud AI applications, and the AI blinky category remains wide open at this point. Get in there and give machine learning a try!

Another IoT Debacle: Charter Offers Home Insecurity

January 18, 2020 by Al Williams 38 Comments

If you are a glass-half-empty person, you’ll view Charter’s announcement that they will shutter their home security and smart home service on February 5th as another reason not to buy into closed-source IoT devices. If you are a glass-half-full person though, you’ll see the cable company’s announcement as a sign that a lot of Zigbee hardware will soon flood the surplus market. Ars Technica reports that after investigation it appears that some of the devices may connect to a standard Zigbee hub after a factory reset, but many others will definitely not.

As you might expect, users were less than thrilled. Especially those that shelled out thousands of dollars on sensors and cameras. This sort of thing might be expected if a company goes out of business, but Charter just doesn’t want to be in the home security business anymore.

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Escher: Etch-a-Sketch As A Service

December 18, 2019 by Tom Nardi 5 Comments

For better or for worse, the tech world has fully committed to pushing as many of their products into “The Cloud” as possible. Of course, readers of Hackaday see right through the corporate buzzwords. It’s all just a fancy way of saying you have to poke some server over the Internet every time you want to use the service. In a way, [Matt Welsh] has perfectly demonstrated this concept with Escher. It’s a normal Etch-a-Sketch, but since somebody else owns it and you’ve got to have an active Internet connection to use it, that makes it an honorary citizen of the Cloud.

Escher takes the form of a 3D printed mount and replacement knobs for the classic drawing toy that allow two NEMA 17 steppers to stand in for human hands. Thanks to the clever design, [Matt] can easily pull the Etch-a-Sketch out and use it the old fashioned way, though admittedly the ergonomics of holding onto the geared knobs might take a little getting used to. But who wants to use their hands, anyway?

In terms of the electronics, the star of the show is the the Adafruit Feather HUZZAH32 development board, paired with a motor controller that can provide 12 V to the steppers. [Matt] even went through the trouble of making a custom voltage regulator PCB that steps down the stepper’s voltage to 5 V for the Feather. Totally unnecessary, just how we like it.

For the software folks in the audience, [Matt] goes into considerable detail about how he got his hardware talking to the web with Google Firebase. Even if the Internet of Sketches doesn’t quite tickle your fancy, we imagine his deep-dive on pushing G-Code files from the browser into the Feather will surely be of interest.

It probably will come as little surprise to hear this isn’t the first automatic Etch-a-Sketch that’s graced these pages over the years, but this might be the most fully realized version we’ve seen yet.