The Numberwang Badge Brought Cheer To CCCamp 2019

While wandering through CCCamp last weekend, in between episodes of forcing Marmite on the unwary, I ran into the well-known Hackaday.io user [Prof. Fartsparkle]. In a last-minute sprint leading up to the con he built himself the Numberwang badge to join in the colorful after-dark festivities with beautiful board artwork and remarkably enjoyable backlit LED display.

The Numberwang badge itself is a clone of the Adafruit Itsy Bitsy sporting an ATSAMD21G18 CPU and running CircuitPython. It has an LED strip on the reverse shining through the bare FR4 as a diffuser, and the Numberwang effect of selecting random numbers is achieved by a host of random touchable numbers sprinkled across its front. For something he freely admits was a last minute project, we think he’s done a pretty good job!

For those mystified by Numberwang, it is a fictional gameshow from a BBC TV comedy programme that involves contestants answering the quizmaster with random numbers. It joins a rich tradition of such hilarious nonsense, and has as a result become cult television.

If you’re really getting into Numberwang, don’t forget that it’s inspired a programming language.

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CCCamp: 5,000 Hackers Out Standing In Their Field

What do hackers do on vacation? What do hackers do whenever they have free time? What do you love to do? That’s right. But how much more fun would it be if you could get together with 5,000 other hackers, share your crazy projects and ideas, eat, drink, dance, swim, and camp out all together for five days, naturally with power and Internet? That’s the idea of the Chaos Communication Camp, and it’s a once-in-four-years highlight of hacker life.

Held not too far outside of Berlin, the Camp draws heavily on hackers from Europe and the UK, but American hackers have been part of the scene since almost the beginning. (And Camp played an important role in the new-wave hackerspaces in the US, but that’s another story.) It’s one thing to meet up with the folks in your local hackerspace and work together on a project or brainstorm the next one, but it’s entirely a different thing when you’re drawing on hackers from all over the world. There was certainly more to see and do at Camp than you could in a month, not to mention in only five days, and this could be overwhelming. But if you dig in, the sense of community that came from shared effort and shared interests was the real take-home. And nearly everything at Camp should have its own article on Hackaday.

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Hackaday Podcast 033: Decompressing From Camp, Nuclear Stirling Engines, Carphone Or Phonecar, And ArduMower

Hackaday Editors Mike Szczys and Elliot Williams are back from Chaos Communication Camp, and obviously had way too much fun. We cover all there was to see and do, and dig into the best hacks from the past week. NASA has a cute little nuclear reactor they want to send to the moon, you’ve never seen a car phone quite like this little robot, and Ardupilot (Ardurover?) is going to be the lawn mowing solution of the future. Plus you need to get serious about debugging embedded projects, and brush up on your knowledge of the data being used to train facial recognition neural networks.

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!

Direct download (64 MB)

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Hands-On: CCCamp2019 Badge Is A Sensor Playground Not To Be Mistaken For A Watch

Last weekend 5,000 people congregated in a field north of Berlin to camp in a meticulously-organized, hot and dusty wonderland. The optional, yet official, badge for the 2019 Chaos Communication Camp was a bit tardy to proliferate through the masses as the badge team continued assembly while the camp raged around them. But as each badge came to life, the blinkies that blossomed each dusk became even more joyful as thousands strapped on their card10s.

Yet you shouldn’t be fooled, that’s no watch… in fact the timekeeping is a tacked-on afterthought. Sure you wear it on your wrist, but two electrocardiogram (ECG) sensors for monitoring heart health are your first hint at the snoring dragon packed inside this mild-mannered form-factor. The chips in question are the MAX30001 and the MAX86150 (whose primary role is as a pulse sensor but also does ECG). We have high-res ADCs just waiting to be misused and the developers ran with that, reserving some of the extra pins on the USB-C connector for external devices.

There was a 10€ kit on offer that let you solder up some electrode pads (those white circles with gel and a snap for a solid interface with your body’s electrical signals) to a sacrificial USB-C cable. Remember, all an ECG is doing is measuring electrical impulses, and you can choose how to react to them. During the workshop, one of the badge devs placed the pads on his temples and used the card10 badge to sense left/right eye movement. Wicked! But there are a lot more sensors waiting for you on these two little PCBs.

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The Tens Of Millions Of Faces Training Facial Recognition; You’ll Soon Be Able To Search For Yourself

In a stiflingly hot lecture tent at CCCamp on Friday, Adam Harvey took to the stage to discuss the huge data sets being used by groups around the world to train facial recognition software. These faces come from a variety of sources and soon Adam and his research collaborator Jules LaPlace will release a tool that makes these dataset searchable allowing you to figure out if your face is among the horde.

Facial recognition is the new hotness, recently bubbling up to the consciousness of the general public. In fact, when boarding a flight from Detroit to Amsterdam earlier this week I was required to board the plane not by showing a passport or boarding pass, but by pausing in front of a facial recognition camera which subsequently printed out a piece of paper with my name and seat number on it (although it appears I could have opted out, that was not disclosed by Delta Airlines staff the time). Anecdotally this gives passengers the feeling that facial recognition is robust and mature, but Adam mentions that this not the case and that removed from highly controlled environments the accuracy of recognition is closer to an abysmal 2%.

Images are only effective in these datasets when the interocular distance (the distance between the pupils of your eyes) is a minimum of 40 pixels. But over the years this minimum resolution has been moving higher and higher, with the current standard trending toward 300 pixels. The increase is not surprising as it follows a similar curve to the resolution available from digital cameras. The number of faces available in data sets has also increased along a similar curve over the years.

Adam’s talk recounted the availability of face and person recognition datasets and it was a wild ride. Of note are data sets by the names of Brainwash Cafe, Duke MTMC (multi-tracking-multi-camera),  Microsoft Celeb, Oxford Town Centre, and the Unconstrained College Students data set. Faces in these databases were harvested without consent and that has led to four of them being removed, but of course, they’re still available as what is once on the Internet may never die.

The Microsoft Celeb set is particularly egregious as it used the Bing search engine to harvest faces (oh my!) and has associated names with them. Lest you think you’re not a celeb and therefore safe, in this case celeb means anyone who has an internet presence. That’s about 10 million faces. Adam used two examples of past CCCamp talk videos that were used as a source for adding the speakers’ faces to the dataset. It’s possible that this is in violation of GDPR so we can expect to see legal action in the not too distant future.

Your face might be in a dataset, so what? In their research, Adam and Jules tracked geographic locations and other data to establish who has downloaded and is likely using these sets to train facial recognition AI. It’s no surprise that the National University of Defense Technology in China is among the downloaders. In the case of US intelligence organizations, it’s easier much easier to know they’re using some of the sets because they funded some of the research through organizations like the IARPA. These sets are being used to train up military-grade face recognition.

What are we to do about this? Unfortunately what’s done is done, but we do have options moving forward. Be careful of how you license images you upload — substantial data was harvested through loopholes in licenses on platforms like Flickr, or by agreeing to use through EULAs on platforms like Facebook. Adam’s advice is to stop populating the internet with faces, which is why I’ve covered his with the Jolly Wrencher above. Alternatively, you can limit image resolution so interocular distance is below the forty-pixel threshold. He also advocates for changes to Creative Commons that let you choose to grant or withhold use of your images in train sets like these.

Adam’s talk, MegaPixels: Face Recognition Training Datasets, will be available to view online by the time this article is published.

UbaBOT Mixes Up 50 Cocktails To Quench CCCamp Thirst

[Steffen Pfiffner’s] tent during the Chaos Communication Camp is full of happiness delivered by something greater than alcohol alone. He’s brought a robot bartender that serves up a show while mixing up one of about 50 cocktail recipes.

The project is the work of five friends from Lake Constance (Bodensee) in southern Germany, near the borders with Switzerland and Austria. It started, as many projects do, with some late night drinking. The five were toiling to mix beverages more complex than your most common fare, and decided to turn their labors instead to robot making.

Since 2012, the project has gone through five revisions, the most recent of which the team calls Uba BOT. Delightfully, the cup tray which moves left and right on the front of the machine is connected using a strain gauge. This provides a way for the robot to sense the presence of a cup to avoid dispensing ingredients all over the bar itself. It also provides a feedback loop that verifies the amount of liquids and volume of ice added to the cup. Once everything’s in the cup, a rotary milk frother lowers itself into position to stir things up a bit.

A Raspberry Pi is in control of eighteen pumps that dispense both liquor and mixers. The team is still trying to work out a way to reliably dispense carbonated mixers, which so far have been a challenge due to over-excited foam. The software was originally based on Bartendro, but has since taken on a life of its own as these things often do. The first time you want a drink, you register an RFID tag and record your height, weight, and age which keeps track of your estimated blood alcohol content based on time and your number of visits to the robot. The firmware also tracks the state of each ingredient to alert a meat-based bar attendant of when a bottle needs replacing.

Join us after the break to see an explanation of what’s under the hood and to watch Uba BOT mix up a Mai Tai.

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