Huge PalmOS Development Archive Goes Online, Thanks To Personal Backups

Palm OS, an operating system for a range mobile devices that predated mobile phones, is largely forgotten today. Or at least, that’s what [Aaron Ardiri] thought.

That all changed when he was contacted by a developer about some Palm OS software he had written decades ago. He soon realized there was a whole community of enthusiasts enthusiastically exploring a platform he had assumed was a forgotten layer in the strata of early mobile computing history.

This led [Aaron] to dust off and publish his substantial personal archive of development tools, source code, documentation, and more all related to his years of working with Palm OS in the early days of mobile computing.

When it comes to the importance of preserving computing history, we can’t put it better than [Aaron] himself so we’ll just quote him here:

Preservation is not simply about keeping old files. Source code, tools and documentation provide a record of how engineers solved problems under the constraints of their time. They also preserve knowledge that is easily lost when companies disappear and platforms are discontinued.

In many ways, Palm OS devices like the PalmPilot have very little in common with modern mobile computing platforms. They had to do more with less, and development reflected that. If you’re curious what these devices were like, here’s a great tour that includes a browser-based emulator.

DIY WiFi Analyzer Sniffs Out Congestion And Coverage Issues, Suggests Fixes

[Roni Bandini]’s JEV WiFi Analyzer is an interesting experiment that glues together a single-board Linux computer, a USB WiFi adapter, and a specialized AI model to create a new kind of automated tool that passively monitors WiFi activity to measure and profile coverage, congestion, and suggest possible optimizations.

Here’s how it works: a Python program connects to WiFi, cycles through available channels, and uses scapy to gather details like signal strength, number of clients, WiFi frames per second, and similar data about each given channel. That data is fed to Jev, a highly efficient sort of decision-making AI model responsible for interpreting that data on an ongoing basis.

Briefly, Jev is a new kind of AI that is completely unable to generate text or images. It outputs only numbers representing bounded decisions. We covered these decision-making models earlier, including locally-installed versions. Jev is cheap enough to throw at a variety of problems, but it’s also practical to run your own model on your own hardware.

In [Roni]’s analyzer, Python gathers the raw numbers and Jev takes care of classifying the WiFi network’s coverage, congestion level, and basic remedial actions if applicable. There’s a brief video embedded below (Spanish only) that shows the Jev WiFi Analyzer in action.

The AI isn’t making particularly deep analyses, but it doesn’t take much to imagine Jev taking a more active role like deciding which channels to spend more (or less) time monitoring. Using a decision-making model in this way is interesting, and makes us wonder if similar models integrated with other kinds of hardware is a branch of projects waiting to happen.

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Learn To Edit STL Files In Just A Few Minutes

Sometimes an STL file needs a bit of editing, but if one doesn’t already know how to use a mesh editor it’s unlikely that one has the time to sit down and learn it in the middle of a project. Happily, that’s where [Prusa]’s five-minute guide to editing STL files directly will come in handy.

The editor of choice is Blender, a fantastic piece of open source software that can be intimidating because it’s got one of those interfaces in which clicking around with an explorer’s heart just isn’t going to get you very far. Most guides start at learning Blender from scratch, assuming one will be using it to create new 3D models. This guide instead focuses on importing and modifying existing models rather than trying to teach the entire interface. For all the apparent complexity, Blender’s underlying functions are actually quite straightforward and simple to use once one knows the right approach.

Having to make changes to an STL file is something most folks have grimaced inwardly about at least once when 3D printing. Certainly, STL files can be imported into CAD programs like FreeCAD, but editing them that way is always a bit of a square peg in a round hole.

A guide like this is a valuable reference for the next time an STL file needs some changes, but the time has not yet come to sit down with a gallon of coffee and learn Blender from scratch.

VR Headset Ditches The Base Stations With DIY Tracking

Those in the virtual reality scene might be interested in [Prohurtz]’s add-on for the Bigscreen Beyond VR headset. BSB-SLAM adds SLAM (Simultaneous Localization and Mapping) tracking to the headset by attaching a sensor to the front of the headset, and providing the software to tie the two together. As a result, the headset can be fully tracked in 3D space with no need for external base stations. It essentially adds inside-out tracking as a DIY add-on.

An early version, shared with a brief video demo posted to X.

Just to be clear, that doesn’t mean the headset becomes wireless. The Beyond connects to a PC, essentially acting as a display, and that part is the same. But it does mean the headset is no longer tied to having to work in a room with base stations pre-installed.

[Prohurtz]’s solution does this by adding a small off-the-shelf Xvisio XR50 board, USB cable, and 3D-printed mount to the unit. The headset works as normal, just with some extra software needed to use the sensor data in lieu of the base stations.

As far as sensors go the Xvisio XR50 is a bit spendy, but the fact that a small and lightweight SLAM sensor that’s capable of delivering positioning data suitable for tracking a headset in near real-time can be bought online and so readily adapted is pretty interesting.

[Prohurtz] got the idea working back in 2025 but it’s now at the point where one can order a part, print an adapter, and be off to the races with a software package.

This isn’t [Prohurtz]’s first time with VR hardware, either. The EyeTrackVR eye tracking add-on is also their work, combining largely off-the-shelf hardware into an effective DIY solution for VR use.

Hairy Armor For Combat Robot? It’s Not Terrible!

[Angus] of Maker’s Muse enjoys combat robotics, in which contenders zip about in an arena, attempting to disable one another with weapons that lift, spin, and smash. He got a funny idea a short while ago and wondered whether a stiff mane of bristles could serve as lightweight, ablative, impact resistant armor?

Just to set the stage, [Angus]’s new robot competes in the plastic antweight (or “plant”) division, in which robots are limited to 150 grams with both chassis and weapons made of plastic. In such circumstances, one can see how a mane of thick, rigid “hairs” might actually punch above its weight, so to speak.

The green shape at the bottom is a spinning weapon. The bristles cover the sides and rear.

Nothing settles a question like a good experiment, so [Angus] sat down and redesigned his latest robot to replace its outer shell with a thick wad of bristles, in the style of a 3D printed lion’s mane. Filament is bridged between the model and an outer support structure, which is cut away afterwards to expose the “hairs”.

How well did it perform? Well enough to merit further study! Where past robots got their outer shells broken up, the hairy robot seems to have come through quite intact. It seems the idea might not be as silly as it first seemed, at least in the plastic antweight division.

3D printers have been fantastic in the field of combat robotics. First they were great because they made custom parts easier and more accessible to hobbyists, but things have evolved more since then. Now folks compete by putting motors and electronics inside almost entirely 3D printed robots. There’s never been a better time to get into combat robotics, and experiment with unorthodox designs.

If you want to try a hairy robot for yourself, be sure to watch the followup in which [Angus] improves the hair-generating process considerably.

Clotty The Custom Period Tracker Can, Of Course, Run DOOM

[kati]’s Clotty might run DOOM and game-ify the menstrual tracking process with a playful Tamagotchi-like aspect, but don’t let that distract you. It is, at its heart, a personal menstrual cycle tracking device that is defined as much by what it does do as what it doesn’t.

Clotty brings a Tamagotchi-like playfulness to the table.

What doesn’t it do? Well, it will never quietly upload one’s menstrual tracking data to a remote server. Nor will it harvest, mishandle, disclose, or sell that same data. Shamefully, that alone sets it far apart from the wide range of period tracking services and apps out there. Also setting it apart is its cheerful lack of discretion. As [kati] puts it, she wanted Clotty’s design to scream “HELLO I AM A PERIOD TRACKING DEVICE” and at this she absolutely succeeded.

Clotty uses an RP2040, color LCD display, and a small variety of sensors built into a palm-sized, uterus-shaped PCB complete with touchpad ovaries. Right now it’s still in its early stages, and basically at the point that everything works hardware-wise and the essentials are there for software, but it’s still in active development. Keep an eye on Clotty’s GitHub repository for updates as features get fleshed out.

Of course, as [kati] observes, the core validity of a device can be defined by whether it can run DOOM, which of course Clotty can. You can find [kati]’s fork of RP2040-DOOM here.

[kati] has a knack for designing effective hardware that gamifies functions and incorporates a playfulness to the design that’s a delight to see. Take a moment to check out her Slightly Sentient D20 which is another excellent example of the kind of work she does.

Birduino Plays Bird Calls On Demand With NFC-enabled Cards

All [Hannah Robertson]’s Birduino needs is for one to tap an NFC-enabled card to the reader, and the device plays one of the vocalizations associated with the bird shown on the card. It ties together a few different components into a whole, and acts as a good reference design for similar work. There are a few time-saving construction tips worth keeping in mind, too.

The major components are an Arduino Nano, an RC522 RFID reader, and an MP3 player module. Using hardware modules and breakout boards means simpler wiring and being able to take advantage of existing libraries and sample code. There are also a few other things in this build that avoid re-inventing the wheel.

A deck of bird cards plus a roll of NFC stickers equals a ready-to-scan assortment without having to design it oneself.

Rather than design, print, and cut a set of bird cards, [Hannah] found a set of bird-themed playing cards with a different North American bird on each. The back of each card gets an NFC sticker off a big roll purchased online. The result? A set of NFC-enabled bird cards with a minimum of work and fuss. The RC522 RFID reader doesn’t fully support NFC, but it works well enough to read the ID off the stickers.

When the user touches a card to the reader, the device plays one of the vocalizations from a collection of sounds for each bird. Creating the manifests and linking each card’s ID to them was a lot of manual work, but the result is great. The sound themselves come from the Cornell Guide to Bird Sounds of the United States and Canada, a $20 USD curated compilation of vocalizations from a staggering 908 bird species of North America. In a way, the biggest bottleneck is the card deck itself. At 52 cards plus two Jokers, it contains only a small subset of the total birds in the Cornell collection.

The enclosure is laser-cut clear acrylic, and here [Hannah] offers some time- and money-saving advice for anyone looking to glue acrylic to acrylic in a way that doesn’t frost or cloud the clear acrylic: Clear Gorilla Glue Gel. There are of course other glues made for this purpose, but Clear Gorilla Glue Gel (the one in a squeeze tube) is something one should be able to find in just about any hardware store. Another tip: double-check before buying, because many Gorilla Glue products are very similarly named despite being significantly different products.

Watch (and listen to) the video embedded below. If birds and their vocalizations are something that intrigues and inspires you, Cornell also has a resource for identifying birds by sound alone — we’ve seen it implemented with a Raspberry Pi and USB microphone.

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