At Three Grand A Tail Light, There’s An Opportunity For A Hacker

It can be amusing sometimes, to read an incredulous reaction from outside our community to something that would be bread-and-butter in most hackerspaces. Take the sorry saga of the Cadillac XLR tail light, as reported by Jalopnik. This car was a more-expensive Corvette with a bit of lard around its midriff, and could appear a tempting pick for a bit of inexpensive luxury rubber-burning were it not for the revelation that a replacement second-hand tail light for one of these roadsters can set you back as much as three grand. The trusty auto on the drive outside where this is being written cost around a tenth that sum, so what on earth is up? Is it because a Caddy carries some cachet, or is something else at play?

It appears that the problem lies in the light’s design. It’s an LED unit, with surface mount parts and a set of fragile internal PCBs that are coated in something that makes reworking them a challenge. On top of that, the unit is bonded together, and instead of being a traditional on-off tail light it’s a microprocessor-controlled device that gets its orders digitally. This is all too much for XLR owners and for the Jalopnik hacks, who castigate General Motors for woefully inadequate design and bemoan the lack of alternatives to the crazy-expensive lights, but can’t offer an alternative.

Reading about the problem from a hardware hacker perspective they are right to censure the motor manufacturer for an appalling product, but is there really nothing that can be done? Making off-the-shelf microcontroller boards light up LEDs is an elementary introduction project for our community, and having the same boards talk to a car’s computer via CAN is something of a done deal. Add in LED strips and 3D printing to create a new backing for the tail light lens, and instead of something impossibly futuristic, you’re doing nothing that couldn’t be found in hackerspaces five years ago.

So what’s to be learned from the Cadillac XLR tail light? First of all, there’s scope for an enterprising hacker to make a killing on a repair kit for owners faced with a three grand bill. Then, there’s another opportunity for us to be acquainted with the reality that the rest of the world hasn’t quite caught up with repair culture as we might imagine. And finally there’s the hope that a badly designed automotive component might just be the hook by which the issue of designed-in obsolescence moves up the agenda in the public consciousness. After all, there will be other similar stories to come, and only bad publicity is likely to produce a change in behavior.

Of course, to get it really right you need a car that’s hackable in the first place. Or better still, one designed by and for hackers.

Thanks [str-alorman] for the tip.

Cadillac XLR header image:Rudolf Stricker [CC BY-SA 3.0].

The Smart Home Gains An Extra Dimension

With an ever-growing range of smart-home products available, all with their own hubs, protocols, and APIs, we see a lot of DIY projects (and commercial offerings too) which aim to provide a “single universal interface” to different devices and services. Usually, these projects allow you to control your home using a list of devices, or sometimes a 2D floor plan. [Wassim]’s project aims to take the first steps in providing a 3D interface, by creating an interactive smart-home controller in the browser.

Note: this isn’t just a rendered image of a 3D scene which is static; this is an interactive 3D model which can be orbited and inspected, showing information on lights, heaters, and windows. The project is well documented, and the code can be found on GitHub. The tech works by taking 3D models and animations made in Blender, exporting them using the .glTF format, then visualising them in the browser using three.js. This can then talk to Hue bulbs, power meters, or whatever other devices are required. The technical notes on this project may well be useful for others wanting to use the Blender to three.js/browser workflow, and include a number of interesting demos of isolated small key concepts for the project.

We notice that all the meshes created in Blender are very low-poly; is it possible to easily add subdivision surface modifiers or is it the vertex count deliberately kept low for performance reasons?

This isn’t our first unique home automation interface, we’ve previously written about shAIdes, a pair of AI-enabled glasses that allow you to control your devices just by looking at them. And if you want to roll your own home automation setup, we have plenty of resources. The Hack My House series contains valuable information on using Raspberry Pis in this context, we’ve got information on picking the right sensors, and even enlisting old routers for the cause.

Hackaday Links: December 29, 2019

The retrocomputing crowd will go to great lengths to recreate the computers of yesteryear, and no matter which species of computer is being restored, getting it just right is a badge of honor in the community. The case and keyboard obviously playing a big part in that look, so when a crowdfunding campaign to create new keycaps for the C64 was announced, Commodore fans jumped to fund it. Sadly, more than four years later, the promised keycaps haven’t been delivered. One disappointed backer, Jim Drew, decided he was sick of waiting, so he delved into the world of keycaps injection molding and started his own competing campaign. Jim details his adventures in his Kickstarter Indiegogo campaign, which makes for good reading even if you’re not into Commodore refurbishment. Here’s hoping Jim has better luck than the competition did.

Looking for anonymity in our increasingly surveilled world? You’re not alone, and in fact, we predict facial recognition spoofing products and methods will be a growth industry in the new decade. Aside from the obvious – and often illegal – approach of wearing a mask that blocks most of the features machine learning algorithms use to quantify your face, one now has another option, in the form of a colorful pattern that makes you invisible to the YOLOv2 algorithm. The pattern, which looks like a soft-focus crowd scene rendered in Mardi Gras colors, won’t make the algorithm think you’re someone else, but it will prevent you from being classified as a person. It won’t work with any other AI algorithm, but it’s still an interesting phenomenon.

We saw a great hack come this week about using an RTL-SDR to track down a water leak. Clayton’s water bill suddenly skyrocketed, and he wanted to track down the source. Luckily, his water meter uses the encoder receive-transmit (ERT) protocol on the 900 MHz ISM band to report his usage, so he threw an SDR dongle and rtlamr at the problem. After logging his data, massaging it a bit with some Python code, and graphing water consumption over time, he found that water was being used even when nobody was home. That helped him find the culprit – leaky flap valves in the toilets resulting in a slow drip that ran up the bill. There were probably other ways to attack the problem, but we like this approach just fine.

Are your flex PCBs making you cry? Friend of Hackaday Drew Fustini sent us a tip on teardrop pads to reduce the mechanical stress on traces when the board flexes. The trouble is that KiCad can’t natively create teardrop pads. Thankfully an action plugin makes teardrops a snap. Drew goes into a bit of detail on how the plugin works and shows the results of some test PCBs he made with them. It’s a nice trick to keep in mind for your flexible design work.

36C3: Open Source Is Insufficient To Solve Trust Problems In Hardware

With open source software, we’ve grown accustomed to a certain level of trust that whatever we are running on our computers is what we expect it to actually be. Thanks to hashing and public key signatures in various parts in the development and deployment cycle, it’s hard for a third party to modify source code or executables without us being easily able to spot it, even if it travels through untrustworthy channels.

Unfortunately, when it comes to open source hardware, the number of steps and parties involved that are out of our control until we have a final product — production, logistics, distribution, even the customer — makes it substantially more difficult to achieve the same peace of mind. To make things worse, to actually validate the hardware on chip level, you’d ultimately have to destroy it.

On his talk this year at the 36C3, [bunnie] showed a detailed insight of several attack vectors we could face during manufacturing. Skipping the obvious ones like adding or substituting components, he’s focusing on highly ambitious and hard to detect modifications inside an IC’s package with wirebonded or through-silicon via (TSV) implants, down to modifying the netlist or mask of the integrated circuit itself. And these aren’t any theoretical or “what if” scenarios, but actual possible options — of course, some of them come with a certain price tag, but in the end, with the right motivation, money is only a detail.

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Turning Sounds From A Flute Into Sheet Music

Composing music can be quite difficult – after all, you have to keep in mind all of the elements of musical theory, from time signature and key signature to the correct length for all of the notes. A team of students from Cornell University’s Designing with Microcontrollers class developed a solution for this problem by transcribing sounds from a flute into sheet music.

The project doesn’t simply detect the notes played – it is able to convert the raw audio into a standardized music score complete with accurate note timings and beats per minute. Before transcribing the music, some audio processing was necessary. The team chose to use a Sallen-Key filter to amplify the raw audio input due to its complex conjugate poles. They then used a fast Fourier Transform (FFT) to determine the frequency for the input note, converting the signal from the time domain to the frequency domain.

The algorithm samples the data to generate an input signal, using the ADC on the microcontroller to receive input from the microphone. It takes the real and imaginary components of the sampled signals and outputs a pair of real and imaginary amplitude components corresponding to the sampled frequency, evenly spaced from 0 to the Nyquist rate (half the sampling rate). The spacing of these bins and the bin with the largest amplitude are used to convert the signal back to a real frequency and a MIDI note.

The system uses a PIC32 for the logic. The circuitry for the microphone amplification uses a non-inverting op-amp with a gain of 50 to increase the microphone output signal amplitude from 15 mV to 750 mV to use by the microcontroller’s ADC. The signal is then sent to the anti-aliasing Sallen-Key filter, with a pole at 2.5 kHz and a Q of 1. The frequency was chosen since the FFT samples at 8 kHz and the frequency corresponds to a note out of the range of a flute. As for the filters, only the low pass filter was implemented in hardware.  While a bandpass filter could have been implemented in hardware, the team decided on a cleaner software approach.

The project is well-documented on the team’s project page, and it’s certainly worth checking out for more detailed discussions on the keypad controls and the software side of the audio processing. If you want to learn more about the FFT, check out this 2016 Hackaday Prize entry for an FFT spectrum analyezer.

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36C3: Phyphox – Using Smartphone Sensors For Physics Experiments

It’s no secret that the average smart phone today packs an abundance of gadgets fitting in your pocket, which could have easily filled a car trunk a few decades ago. We like to think about video cameras, music playing equipment, and maybe even telephones here, but let’s not ignore the amount of measurement equipment we also carry around in form of tiny sensors nowadays. How to use those sensors for educational purposes to teach physics is presented in [Sebastian Staacks]’ talk at 36C3 about the phyphox mobile lab app.

While accessing a mobile device’s sensor data is usually quite straightforwardly done through some API calls, the phyphox app is not only a shortcut to nicely graph all the available sensor data on the screen, it also exports the data for additional visualization and processing later on. An accompanying experiment editor allows to define custom experiments from data capture to analysis that are stored in an XML-based file format and possible to share through QR codes.

Aside from demonstrating the app itself, if you ever wondered how sensors like the accelerometer, magnetometer, or barometric pressure sensor inside your phone actually work, and which one of them you can use to detect toilet flushing on an airplane and measure elevator velocity, and how to verify your HDD spins correctly, you will enjoy the talk. If you just want a good base for playing around with sensor data yourself, it’s all open source and available on GitHub for both Android and iOS.

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Analog Meter Clock Uses Parts From A Simpler Time

Clocks with hands that turn are all well and good for the common folk, but hacker types prefer something different. [Sjm4306] is one such person, and developed this analog dial clock with parts we’d almost consider retro by modern standards.

The microcontroller at the heart of the build is a PIC16F886. An 8-bit micro from the Microchip brand, it features no Arduino bootloader or USB interface, being flashed via a dedicated programmer. This is combined with a DS1302 real-time clock to keep accurate time, and a MCP4922 DAC which is responsible for generating the output to drive the dials. The dials themselves are sourced from eBay, being simple voltmeters. They’re given a new backing to display hours and minutes instead of volts, and backlit with LEDs for style.

In this day and age, we’re more used to seeing high-end micros used with integrated DACs and USB programming, but it’s nice to see the parts of yesteryear being used, too. It’s not the first clock we’ve seen from [sjm4306], either. Video after the break.

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