While robots enter other industries in herds, the assembly of garments has long been a tedious, human privilege. Now, for the first time, a robot has sewn an entire, wearable piece of garment. Sewbo, an industrial robot programmed to tackle the tricky task, assembles clothes and makes it look easy.
Your local hardware store or garden supply center probably has everything you need to install landscape lighting all around your property. What’s a little less likely is coming out of that situation with fewer holes in your wallet than in your yard. And even then, it’s pretty much guaranteed that any off-the-shelf equipment won’t send you a text message when your landscape lighting isn’t working properly. [Mark]’s landscape lighting system does, though!
Powered by a Raspberry Pi, this landscape lighting system has every feature imaginable. It can turn the lighting on at sunset and turn it off at a set or random time later in the evening. There’s a web interface served from the Pi that allows further user control. The Raspberry Pi also monitors the lighting and can sense when one of the lights burns out. When one does, the Pi uses Twillo to send a text message notification.
There’s not many more features we can imagine packing into a setup like this. Of course, if you don’t have a spare Pi around you can probably manage to get the job done with an ESP8266, or even an old-fashioned Arduino.
If it wasn’t for the weird Dutch-Norwegian techno you’d presumably have to listen to forever, [Gianni B.]’s doll house for his daughter, [Rita] makes living in a Barbie World seem like a worthwhile endeavor. True to modern form, it’s got LED lighting. It’s got IoT. It’s got an app and an elevator. It even has a tiny, working, miniature television.
It all started with a Christmas wish. [Rita] could no longer stand to bear the thought of her Barbie dolls living a homeless lifestyle on her floor, begging passing toys for enough monopoly money to buy a sock to sleep under. However, when [Gianni] visited the usual suspects to purchase a dollhouse he found them disappointing and expensive.
So, going with the traditional collaborating-with-Santa ruse, he and his family had the pleasure of collaborating on a dollhouse development project. Each room is lit by four ultra bright LEDs. There is an elevator that’s controlled by an H-bridge module, modified to have electronic braking. [Rita] doesn’t own a Dr. Barbie yet, so safety is paramount.
The brain of the home automation is a PIC micro with a Bluetooth module. He wrote some code for it, available here. He also went an extra step and used MIT’s scratch to make an app interface for the dollhouse. You can see it work in the video after the break. The last little hack was the TV. An old arduino, an SD Card shield, and a tiny 2.4 inch TFT combine to make what’s essentially a tiny digital picture frame.
His daughter’s are overjoyed with the elevation of their doll’s economic class and a proud father even got to show it off at a Maker Faire. Very nice!
[Ken Rumer] bought a new house. It came with a troublingly complex pool system. It had solar heating. It had gas heating. Electricity was involved somehow. It had timers and gadgets. Sand could be fed into one end and clean water came out the other. There was even a spa thrown into the mix.
Needless to say, within the first few months of owning their very own chemical plant they ran into some near meltdowns. They managed to heat the pool with 250 dollars of gas in a day. They managed to drain the spa entirely into the pool, but thankfully never managed the reverse. [Ken] knew something had to change. It didn’t hurt that it seemed like a fun challenge.
The first step was to tear out as much of the old control system as could be spared. An old synchronous motor timer’s chlorine rusted guts were ripped out. The solar controler was next to be sent to its final resting place. The manual valves were all replaced with fancy new ones.
Rather than risk his fallible human state draining the pool into the downstairs toilet, he’d add a robot’s cold logical gatekeeping in order to protect house and home. It was a simple matter of involving the usual suspects. Raspberry Pi and Arduino Man collaborated on the controls. Import relay boards danced to their commands. A small suite of sensors lent their aid.
Now as the soon-to-be autumn sun sets, the pool begins to cool and the spa begins to heat automatically. The children are put to bed, tired from a fun day at the pool, and [Ken] gets to lounge in his spa; watching the distant twinkling of lights on his backyard industrial complex.
Automation makes the world go around. Whether it’s replacing elevator attendants with buttons, replacing songwriters with computer algorithms, or giving rovers on Mars the same sense and avoid capability as a Tesla, Automation makes our lives easier and better. Today we’re excited to announce the twenty projects that best demonstrate the possibilities of Automation in the running for the 2016 Hackaday Prize. These projects tackled problems ranging from improving the common stepper motor to flying Lidar around a neighborhood on a gigantic ducted fan.
The winners of the Hackaday Prize automation challenge are, in no particular order:
- HeadsUp, A Low-Cost Device To Diagnose Concussions
- Self Replicating CNC For 194 (Or More) Countries
- 3D Printable Portable Slit Lamp
- Alarm Detection For Hearing Impaired
- Automated LED/Laser Diode Analysis and Modeling
- sdramThingZero – 133MS/s 32-Bit Logic Analyzer
- Evive: A Prototyping Platform For Makers
- Mycodo | Environmental Regulation System
- The Julius Project
- Theia IoT Light Switch
- The Distributed Ground Station Network
- Affordable Reflectance Transformation Imaging Dome
- Open Indirect Ophthalmoscope
- Open LIDAR
If your project is on the list, congrats. You just won $1000 for your hardware project, and are now moving up to the Hackaday Prize finals where you’ll have a chance to win $150,000 and a residency at the Supplyframe DesignLab in Pasadena.
If your project didn’t make the cut, there’s still an oppurtunity for you to build the next great piece of hardware for The Hackaday Prize. The Assistive Technologies Challenge is currently under way challenging you to build a project that helps others move better, see better, or live better.
We’re looking for exoskeletons, a real-life Iron Man, a better wheelchair, a digital braille display, or the best educational software you can imagine.
Like the Design Your Concept, Anything Goes, Citizen Science, and Automation rounds of the the Hackaday Prize, the top twenty projects will each win $1000 and move on to the Hackaday Prize finals for a chance to win $150,000 and a residency at the Supplyframe DesignLab in Pasadena
If you don’t have a project up on Hackaday.io, you can start one right now and submit it to the Hackaday Prize. If you’re already working on the next great idea in assistive technologies, add it to the Assistive Technologies challenge using the dropdown menu on the sidebar of your project page.
The Hackaday Prize is the greatest hardware competition on Earth. We want to see the next great Open Hardware project benefit everyone. We’re working toward that by recognizing people who build, make, and design the coolest and most useful devices around.
This Raspberry Pi 2 with computer vision and two solenoid “fingers” was getting absurdly high scores on a mobile game as of late 2015, but only recently has [Kristian] finished fleshing the project out with detailed documentation.
Developed for a course in image analysis and computer vision, this project wasn’t really about cheating at a mobile game. It wasn’t even about a robotic interface to a smartphone screen; it was a platform for developing and demonstrating the image analysis theory he was learning, and the computer vision portion is no hack job. OpenCV was used as a foundation for accessing the camera, but none of the built-in filters are used. All of the image analysis is implemented from scratch.
The game is a simple. Humans and zombies move downward in two columns. Zombies (green) should get a screen tap but not humans. The Raspberry Pi camera takes pictures of the smartphone’s screen, to which a HSV filter is applied to filter out everything except green objects (zombies). That alone would be enough to get you some basic results, but not nearly good enough to be truly reliable and repeatable. Therefore, after picking out the green objects comes a whole chain of additional filtering. The details of that are covered on [Kristian]’s blog post, but the final report for the project (PDF) is where the real detail is.
If you’re interested mainly in seeing a machine pound out flawless victories, the video below shows everything running smoothly. The pounding sounds make it seem like the screen is taking a lot of abuse, but [Kristian] mentions that’s actually noise from the solenoids and not a product of them battling the touchscreen. This setup can be easily adapted to test out apps on different models of phones — something that has historically cost quite a bit of dough.
If you’re interested in the nitty-gritty details of the reasons and methods used for the computer vision portions, be sure to go through [Kristian]’s github repository where everything about the project lives (including the aforementioned final report.)
[Fred Hoefler] was challenged to finally do something with that Raspberry Pi he wouldn’t keep quiet about. So he built a machine assist loom for the hand weaver. Many older weavers simply can’t enjoy their art anymore due to the physical strain caused by the repetitive task. Since he had a Pi looking for a purpose, he also had his project.
His biggest requirement was cost. There are lots of assistive looms on the market, but the starting price for those is around ten thousand dollars. So he set the rule that nothing on the device would cost more than the mentioned single board computer. This resulted in a BOM cost for the conversion that came in well under two hundred dollars. Not bad!
The motive parts are simple cheap 12V geared motors off Amazon. He powered them using his own motor driver circuits. They get their commands from the Pi, running Python. To control the loom one can either type in commands into the shell or use the keyboard. There are also some manual switches on the loom itself.
In the end [Fred] met his design goal, and has further convinced his friends that the words Raspberry Pi are somehow involved with trouble.