For whatever reason, [Jeremy] wants to photograph bees in flight. This is one of those things that doesn’t seem that hard until you try to do it. He’s got the mechanical part that can move the camera as fast as the bee flies. But you still have to point the camera correctly. He considered quite a few methods of acquiring and tracking the bee, but he finally settled on a stereo camera. His requirements also made the camera design challenging. In particular, the bees move fast enough that things like USB transmission times become significant. You can see his solution in the video below.
[Jeremy] does a great job explaining all the tradeoffs between frame rate, resolution, focal length, and other optical issues. Of course, he also wanted a global shutter sensor. Rolling shutter cameras scan row-by-row, creating the well-known “jello effect”. Global shutters capture all pixels at once. That also removes any uncertainty as to “when” the shutter fired.
Paper as a substrate for electronic circuits is not very common, but promising for flexible circuits with low cost and easy recyclability. That said, paper is not an easy material to work with when printing traces, as the cellulose material is both absorbent and irregular, limiting the resolution and accuracy of so-called papertronics. Even when using higher-quality paper with wax-based masks this resulted in poor resolution issues, so [Zahra Rafiee] et al. opted to approach the problem from the other direction, by using hydrophobic parchment paper as the base combined with a laser.
The nice thing about the inks used with papertronics that they aren’t just traces, but can also be functional elements like resistors, which is also demonstrated in the paper. The channels for the inks are created using a 50 Watt CO2 laser, which etches away the silicone coating on the parchment paper. The achieved resolution in the article is around 250 µm for line widths and 300 µm line spacing, which is much better than that for wax-based alternatives.
Avian Visitors is a lovely project by [Teddy Warner] that uses a Raspberry Pi and microphone to keep track of which birds have been visiting your home, and creates a colorful illustration of recent visitors on top of it all.
It reports on a web interface of its own making, but what really takes things to a new level is an optional, stylish E-Ink panel that shows the last 24 hours’ worth of visitors at a glance in a collage.
The key to identification is BirdNET (GitHub here), a deep learning classifier from Cornell that can reliably identify and classify more than 11,000 species worldwide based on sound alone.
Based on that information, the system pulls bird images from a reference set for the region and creates a collage representing the breadth and frequency of visitors in a single image. The larger the image of a bird, the more frequently it was heard.
If you’ve ever worked with produce, you might know about grading. In addition to deciding if, say, a strawberry is good or not, they also have to sort them by color. Turns out, you don’t care if one package of berries is a bit redder than another, but you do care if one package has too much color variation. [Pmalfa31] applied an ESP32 and machine learning to grading tomatoes.
The system knows in advance if you are processing standard tomatoes or cherry tomatoes and uses two different sets of learned data depending on which you select. The program receives raw data from an optical sensor and then processes it to remove empty belt images, compute statistical information, and group readings for a single fruit together.
As someone who disassembles and repairs hardware, [Aad] eventually ended up with a huge collection of mixed bolts and screws. This led to creating the automatic bolt and screw sorting system you see here, although in a way it is just a proof of concept. Bolts and screws happen to be a useful application for now, but the system is capable of sorting just about any small objects.
A bit of machine vision detects the size and shape of each object. Weight can also be measured.
Mixed pieces go onto a large conveyor belt, shown on the right. This feeds a few screws at a time down a chute, where they roll onto an illuminated platform.
Above the lit platform is a camera, and machine vision is used to detect the size and shape and orientation of each screw. A robotic gripper on a gantry picks the screws up one by one — separating them first if they happened to clump together — and places each in a drop-off cart. The cart drops the object into a receptacle with its brethren, making sure similar ones are grouped together. Watch it in action in the video, embedded below the page break.
It’s a great build that shows fancy components aren’t necessary for good results. Servos and steppers are controlled with an ESP32-WROOM board, and a piezo sensor detects screws falling off the conveyor. Some of you may have noticed a repurposed Ultimaker 3D printer serving as the bulk of the system, its hot end having been replaced with a gripper that can raise and lower. The overhead camera is an ESP32-CAM adapted to accept M12 lenses so it can focus on the platform.
There’s one more feature worth mentioning — the system also has the ability to measure the weight of a picked object by placing it onto a moveable inspection platform, which can optionally put it under a USB microscope for a closer look. Everything is controlled by a nearby PC, so there’s a lot of flexibility built into the system.
We suppose that once all the screws and bolts in a shop are sorted, it only makes sense to sort all the nuts. Are there other objects besides screws and bolts that would be useful to sort with a system like this? If you have any ideas, don’t keep them to yourself! [Aad] would love to hear your comments and ideas, so share them below.
We all have that bin in the corner of our shops — the one with all the circuit boards or broken electronics that we are totally gonna do something with. We might rationalize that they’re worth keeping for the parts alone, but the reality is, unless you desolder and sort all the components ahead of time, most of us will never really use these spare parts to their full potential. Except it really doesn’t have to be that way. Junkbin.io is an attempt to improve on the state of that corner bin.
Though in its early years, Junkbin has a variety of the previously mentioned resources as well as many others. Currently, it is ripe to contribute, and we here at Hackaday know how important the community is to get these projects truly off the ground and to their full potential.
Created by [Steve Cap], Junkbin is a community dictionary of sorts to document and reuse electronic components found on many of the devices found around you. Do you need a single small form factor resistor of a specific resistance? That’s where Junkbin comes in to show you where you might find that specific component.
If you want a more macro-scale example of electronics recycling, make sure to check out our other featured projects such as these reused laptops! Or maybe take a look at this graveyard of defunct electronics to add to Junkbin…
There was a particular treat at the recent Electromagnetic Field event in the UK, as [Tim Hunkin] delivered a talk on the history of arcade machines. Given that he’s something of an engineering hero for his many years of delighting us with machines, it’s definitely worth a watch.
He has a special interest in arcade machines given that he runs a pair of arcades featuring his own creations. Part of the history tour explains the influence some machines have had on his creations, from the early automata he starts with, through to the Pachinko machine that graces Novelty Automation in London. We’re introduced to Victorian saucy film viewers, one-armed bandits, and pinball machines, and along the way the secret of that most British of machines, the penny falls, is revealed. We particularly like the rare electromechanical Pepper’s Ghost style video game cabinets he describes.
A few years ago now we took a trip to Novelty Automation, and wrote a profile for its creator. If you’re ever in London or Southwold, we suggest you do too. The video from EMF is below the break.