Hackaday Podcast 115: AI Is Bad At Linux Terminal, Puppeting Pico In Python, 3D Scanning Comes Up Short

Hackaday editors Mike Szczys and Elliot Williams pull back the curtain on a week of excellent hacks. We saw an awesome use of RGB LEDs as a data channel on a drone, and the secrets of an IP camera’s OS laid bare with some neat reverse engineering tools. There’s an AI project for the Linux terminal that guesses at the commands you actually want to run. And after considering how far autopilot has come in the aerospace industry, we jump into a look at the gotchas you’ll find when working with models of 3D scanned objects.

Take a look at the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!

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Food Safe Printing Techniques

One thing that always provokes spirited debate around the Hackaday bunker is just how dangerous is it to use 3D printed plastic in contact with food. We mostly agree it isn’t a good thing, but we also know some people do it regularly and they don’t drop dead instantly, either. [Jakub] decided to do some testing and make some recommendations. There’s even a video explaining the results.

Unlike a lot of what we’ve read about this topic in the past, [Jakub’s] post is well-researched and does actual testing including growing bacteria cultures from cups used for milk. He starts out identifying the EU and US regulations about what you can call food-grade. There’s also recognition that while a base plastic might be safe for contact with food, there’s no way to know exactly what additives and other things are in the plastic to change its properties and color.

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Hackaday Podcast 096: Diaphragm Engine, DIY Dish Washer, Forgotten Soviet Computers, And A Starlink Teardown

Hackaday editors Elliot Williams and Mike Szczys discuss the latest and greatest in geeky goodness. This week we saw a Soviet time capsule come to light with the discovery of a computer lab from a building abandoned in the 1990’s. A two-cycle compressed air engine shatters our expectations of what is involved in RC aircraft design. There’s a new toolkit for wireless hacking on the scene in the form of a revitalized HackRF PortaPack firmware fork. And what goes into dishwasher design? Find out in this exciting episode.

Take a look at the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!

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Actuator Opens The Door To Drier Dishes

Dishwashers are great at washing dishes and even rinsing them, most of the time. Where they tend to fail is in the drying part. Somehow these things dry hot enough to warp stoneware dishes, but not so well that things are actually dry when you open the door. Blame it on the lack of air movement.

Ideally, the dishwasher cycle is started soon after dinner time so it can be finished and opened up before it’s time for bed. But if you do that, then you miss all the dishes from late-night snacking and the occasional wine glass. Wait until bedtime to start it, and it has to sit several hours with moisture inside. Obviously, the answer is to listen for the victory beeps at the end of the cycle, and use a slow but forceful actuator to push the door open.

[Ivan Stepaniuk] is listening for the dishwasher’s frequencies with a microphone, amplifying them with a trusty LM386, and using an STM32 blue pill to crunch the audio. [Ivan] has plans to incorporate an ESP8266 board for IoT, presumably to get a notification when the door has been opened successfully. Check out the demo after the break.

Yes, dishwashers are great until they aren’t, and some little part breaks. But why pay for a new detergent compartment cover when you can just print one?

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Marian Croak Is The MVP Of VoIP Adoption

If you’ve ever used FaceTime, Skype, own a Magic Jack, or have donated money after a disaster by sending a text message, then you have Marian Croak to thank. Her leadership and forward thinking changed how Ma Bell used its reach and made all of these things possible.

Marian Croak is a soft-spoken woman and a self-described non-talker, but her actions spoke loudly in support of Internet Protocol (IP) as the future of communication. Humans are always looking for the next best communication medium, the fastest path to understanding each other clearly. We are still making phone calls today, but voice has been joined by text and video as the next best thing to being there. All of it is riding on a versatile network strongly rooted in Marian’s work.

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Europeans Now Have The Right To Repair – And That Means The Rest Of Us Probably Will Too

As anyone who has been faced with a recently-manufactured household appliance that has broken will know, sometimes they can be surprisingly difficult to fix. In many cases it is not in the interests of manufacturers keen to sell more products to make a device that lasts significantly longer than its warranty period, to design it with dismantling or repairability in mind, or to make spare parts available to extend its life. As hardware hackers we do our best with home-made replacement components, hot glue, and cable ties, but all too often another appliance that should have plenty of life in it heads for the dump.

Czech waste management workers dismantle scrap washing machines. Tormale [CC BY-SA 3.0].
Czech waste management workers dismantle scrap washing machines. Tormale [CC BY-SA 3.0].
If we are at a loss to fix a domestic appliance then the general public are doubly so, and the resulting mountain of electrical waste is enough of a problem that the European Union is introducing new rules governing their repairability. The new law mandates that certain classes of household appliances and other devices for sale within the EU’s jurisdiction must have a guaranteed period of replacement part availability and that they must be designed such that they can be worked upon with standard tools. These special classes include washing machines, dishwashers, refrigerators, televisions, and more.

Let’s dig into the ramifications of this decision which will likely affect markets beyond the EU and hopefully lead to a supply of available parts useful for repair and beyond.

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Data Mining Home Water Usage; Your Water Meter Knows You A Bit Too Well

The average person has become depressingly comfortable with the surveillance dystopia we live in. For better or for worse, they’ve come to accept the fact that data about their lives is constantly being collected and analyzed. We’re at the point where a sizable chunk of people believe their smartphone is listening in on their personal conversations and tailoring advertisements to overheard keywords, yet it’s unlikely they’re troubled enough by the idea that they’d actually turn off the phone.

But even the most privacy-conscious among us probably wouldn’t consider our water usage to be any great secret. After all, what could anyone possibly learn from studying how much water you use? Well, as [Jason Bowling] has proven with his fascinating water-meter data research, it turns out you can learn a whole hell of a lot by watching water use patterns. By polling a whole-house water flow meter every second and running the resulting data through various machine learning algorithms, [Jason] found there is a lot of personal information hidden in this seemingly innocuous data stream.

The key is that every water-consuming device in your home has a discernible “fingerprint” that, with enough time, can be identified and tracked. Appliances that always use the same amount of water, like an ice maker or dishwasher, are obvious spikes among the noise. But [Jason] was able to pick up even more subtle differences, such as which individual toilet in the home had been flushed and when.

Further, if you watch the data long enough, you can even start to identify information about individuals within the home. Want to know how many kids are in the family? Monitoring for frequent baths that don’t fill the tub all the way would be a good start. Want to know how restful somebody’s sleep was? A count of how many times the toilet was flushed overnight could give you an idea.

In terms of the privacy implications of what [Jason] has discovered, we’re mildly horrified. Especially since we’ve already seen how utility meters can be sniffed with nothing more exotic than an RTL-SDR. But on the other hand, his write-up is a fantastic look at how you can put machine learning to work in even the most unlikely of applications. The information he’s collected on using Python to classify time series data and create visualizations will undoubtedly be of interest to anyone who’s got a big data problem they’re looking to solve.