Most of the time, you’ll know where your cats are — asleep on the bed about 23.5 hours a day and eating or pooping the rest of the time. But some cats are more active than others, so there’s commercial options for those who want to keep tabs on their pet. Unfortunately, [Sahas Chitlange] didn’t like any of them, so he designed and built his own open source version: FindMyCat.io.
The system is in two parts: a module that fits onto a cat collar, and a home station that, well, stays at home. It offers a variety of tracking modes. In home mode, the home station signals the collar every 10 seconds, which stays in a deep sleep most of the time. If the collar doesn’t get a signal from the home station, it switches to ping mode, where it will wait for a signal from the FindMyCat over the LTE-M connection and report its location.
Finally, the app can set the collar to Lost Kitteh mode, where the collar will send a location to the app every seven minutes or thirty seconds. The collar also supports a direction-finding feature, using the ultra wideband (UWB) feature of recent Apple iPhones to point you in the direction and distance of the tracked cat.
The collar is built around a Nordic Semiconductor NRF-9160, a System in a Package (SiP) that does most of the heavy lifting as it includes GPS, an LTE-M modem, and an ARM processor. One interesting feature here: [Sahas] doesn’t make his antennas on the PCB, but instead uses an Ignion NN03-310, an off-the-shelf antenna that is already qualified for LTE-M use. That means this system can be connected to almost any LTE-M network without getting yelled at for using unqualified hardware and making the local cell towers explode.
The collar also includes a DWM3001CDK ultrawideband (UWB) module used for the locator feature. The accompanying app uses this and Apple’s UWB support to show the user which direction the cat is in, and how far away it is. The app isn’t in the Apple App Store yet, so you’ll need to sign up for an Apple Developer account to use it. We’d love to hear from anyone who takes it for a test drive with their own pet.
The gaming world experienced a bit of a resurgence in 2020 that is still seen in the present day. Even putting aside the effects from the pandemic, the affordability and accessibility has arguably never been better. Building a gaming PC can have its downsides, though, and a challenging issue to troubleshoot is input lag or input latency. This is something that’s best measured with standalone hardware, and if this is an issue on your setup you may want to take a look at this latency meter.
Unlike other measurement devices that use the time between a mouse button input and the monitor’s display of a bullet or shooting event, this one looks at mouse movement and the change in the scene instead. This makes it much more versatile than other methods since it’s independent of specific actions, and can be used in any game without any specific events needed to perform the measurement. A camera phototransistor is placed on the monitor’s top edge and the Arduino-based device sends mouse commands to the computer while measuring the time between those commands and the shift in the image on the monitor.
The project is open source, so with the right hardware it’s possible to build one to troubleshoot latency issues or just to learn more about a particular hardware configuration’s behavior. Arduinos and other microcontrollers have been doing all kinds of things by pretending to be human interface devices like this for a while now. One of our favorites of late was this effects pedal that replicates musical effects on mice and keyboards.
It’s hard to read the headlines today without feeling like the world couldn’t possibly get much worse. And then tomorrow rolls around, and a fresh set of headlines puts the lie to that thought. On a macro level, there’s not much that you can do about that, but on a personal level, illustrating your news feed with mostly wrong, AI-generated images might take the edge off things a little.
Let us explain. [Roy van der Veen] liked the idea of an e-paper display newsfeed, but the crushing weight of the headlines was a little too much to bear. To lighten things up, he decided to employ Stable Diffusion to illustrate his feed, displaying both the headline and a generated image on a 7.3″ Inky 7-color e-paper display. Every five hours, a script running on a Raspberry Pi Zero 2W fetches a headline from a random source — we’re pleased the list includes Hackaday — and composes a prompt for Stable Diffusion based on the headline, adding on a randomly selected prefix and suffix to spice things up. For example, a prompt might look like, “Gothic painting of (Driving a Motor with an Audio Amp Chip). Gloomy, dramatic, stunning, dreamy.” You can imagine the results.
We have to say, from the examples [Roy] shows, the idea pretty much works — sometimes the images are so far off the mark that just figuring out how Stable Diffusion came up with them is enough to soften the blow. We’d have preferred if the news of the floods in Libya had been buffered by a slightly less dismal scene, but finding out that what was thought to be a “ritual mass murder” was really only a yoga class was certainly heartening.
The design uses half length darts which tend to fly a little nicer from high-powered blasters. It fires them using belts driven by powerful motors, similar to wheel blasters. The darts themselves are loaded into a drum magazine which has sliders to push the darts into the wheels as the drum rotates by.
It all sounds straightforward enough, but getting it all working in harmony is a challenge—particularly at a fire rate of 100 darts per second. The build video explains the trials and tribulations involved in getting near that fire rate, with darts getting shredded and magazines throwing out parts along the way. A good helping of iterative design helps get everything playing nice, with the darts neatly leaving the magazine and flying downrange at great speed. The slow-motion videos of darts flying out of the blaster in rapid succession are a special treat.
Files are available via Onshape for those looking to dive deeper into the design. We’ve seen some other neat Nerf blasters before, too. Video after the break.
As amazing and groundbreaking as the Nintendo 64 was, over the years it has also become synonymous with blurry textures and liberal use of Gouraud shading as its most strongly defining visual features. In a recent video, [James Lambert] covers how the system’s minuscule 4 kB texture memory (TMEM) can be circumvented using mipmapping. By loading progressively more detailed textures (each in 4 kB chunks) in a level-of-detail (LoD), the visual fidelity can be maximized while keeping rendering speeds relatively zippy, as the real-time demo proves.
This project was made for the N64brew 2023, with the source code available on [James]’s GitHub account. Although impressive, it bears noting that mipmapping was not an unknown approach in 1996, and many approaches were used to work around the N64’s physical limitations.
In the case of mipmapping, [James]’s demo perfectly demonstrates the problematic nature of mipmapping, as it dramatically increases the storage requirements for the textures, hitting 40 MB just for this one single room, for a system that supports up to 64 MB cartridges.
Ultimately, this shows that the 4 kB TMEM was not the only issue with the N64, with the limited (and expensive) mask ROMs for the cartridges proving to be an insurmountable obstacle that systems like Sony’s PlayStation largely did not have to contend with. With roomy 650 MB+ optical storage, the PS1 got instead tripped up by the glacial access and loading speeds of optical media and its soggy-potato-powered GPU.
Seeing demonstrations like these manage to wonderfully highlight the bottlenecks in these old consoles, and makes one wonder about what could have been, even in an era before 1 TB solid-state drives and direct resource streaming between GPU and said storage.
Halloween is possibly the hackiest of holidays. Think about it: when else do you get to add animatronic eyes to everyday objects, or break out the CNC machine to cut into squashes? Labor day? Nope. Proximity-sensing jump-scare devices for Christmas? We think not. But for Halloween, you can let your imagination run wild!
We’re happy to announce that DigiKey and Arduino have teamed up for this year’s Hackaday Halloween Contest. Bring us your best costume, your scariest spook, your insane home decorations, your wildest pumpkin, or your most kid-pleasing feat!
We’ll be rewarding the top three with a $150 gift certificate courtesy of DigiKey, plus some Arduino Halloween treats if you use a product from the Arduino Pro line to make your hair-raising fantasy happen.
We’ve also got five honorable mention categories to inspire you to further feats of fancy.
Costume: Halloween is primarily about getting into outrageous costumes and scoring candy. We don’t want to see the candy.
Pumpkin: Pumpkin carving could be as simple as taking a knife to a gourd, but that’s not what we’re after. Show us the most insane carving method, or the pumpkin so loaded with electronics that it makes Akihabara look empty in comparison.
Kid-Pleaser: Because a costume that makes a kid smile is what Halloween is really all about. But games or elaborate candy dispensers, or anything else that helps the little ones have a good time is fair game here.
Hallowed Home: Do people come to your neighborhood just to see your haunted house? Do you spend more on light effects than on licorice? Then show us your masterpiece!
Spooky: If your halloween build is simply scary, it belongs here.
The rise of 3D printing has given us incredible things, from awesome tchotchkes to intricate chocolates to useful things like spare body parts. But none has been so vital to comedy as say, printing hats for sea urchins. That’s right, sea urchins like to cover up with various things and will happily don, say, a 3D printed hat if presented the opportunity.
Inside the large bamboo enclosure is an TTGO that fetches cheaply-obtained tide information and displays it on the screen. The TTGO also controls a servo that moves the sea urchin around. As it moves, a magnet in the urchin’s head (?) attracts the next hat.
Before settling on the current design, [rabbitcreek] experimented with both a sand dollar and a sea urchin skeleton. All the files are available if you want to whip up your own.