The Bus Pirate is one of our favorite tool for quick-and-dirty debugging in the microcontroller world. Essentially it makes it easy to communicate with a wide variety of different chips via a serial terminal regardless of the type of bus that the microcontroller uses. Although it was intended as a time-saving prototyping device, there are a lot of real-world applications where a Bus Pirate can be employed full-time, as [Scott] shows us with his Bus Pirate data logger.
[Scott] needed to constantly measure temperature, and the parts he had on hand included an LM75A breakout board that has a temperature sensor on board. These boards communicate with I2C, so it was relatively straightforward to gather data from the serial terminal. From there, [Scott] uses a Python script to automate the process of gathering the data. The process he uses to set everything up using a Raspberry Pi is available on the project site, including the code that he used in the project.
[Scott] has already used this device for a variety of different projects around his house and it has already proven incredibly useful. If you don’t already have a Bus Pirate lying around there are a few other ways to gather temperature data, but if you have an extra one around or you were thinking about purchasing one, then [Scott]’s project is a great illustration of the versatility of this device.
Recently ZDNet and Gizmodo published articles outlining a critical flaw in a large array of personal printers. While the number of printers with this flaw is staggering, the ramifications are even more impressive. Ultimately, any of these printers could have documents sent to them stolen even if the document was only intended to be printed as a hard copy.
Luckily the people responsible for this discovery are white-hat in nature, and the release of this information has been made public so the responsible parties can fix the security flaws. Whether or not the “responsible party” is the manufacturer of the printer, though, is still somewhat unclear because part of the exploit takes advantage of a standard that is part of almost all consumer-grade printers. The standard itself may need to be patched.
Right now, however, it doesn’t seem clear exactly how deep the rabbit hole goes. We all remember the DDoS attack that was caused by Internet of Things devices that were poorly secured, and it seems feasible that networked printers could take some part in a similar botnet if a dedicated user really needed them. At the very least, however, your printed documents might not be secure at all, and you may be seeing a patch for your printer’s firmware in the near future.
Like any Moore’s Law-inspired race, the megapixel race in digital cameras in the late 1990s and into the 2000s was a harsh battleground for every manufacturer. With the development of the smartphone, it became a war on two fronts, with Samsung eventually cramming twenty megapixels into a handheld. Although no clear winner of consumer-grade cameras was ever announced (and Samsung ended up reducing their flagship phone’s cameras to sixteen megapixels for reasons we’ll discuss) it seems as though this race is over, fizzling out into a void where even marketing and advertising groups don’t readily venture. What happened?
The Technology
A brief overview of Moore’s Law predicts that transistor density on a given computer chip should double about every two years. A digital camera’s sensor is remarkably similar, using the same silicon to form charge-coupled devices or CMOS sensors (the same CMOS technology used in some RAM and other digital logic technology) to detect photons that hit it. It’s not too far of a leap to realize how Moore’s Law would apply to the number of photo detectors on a digital camera’s image sensor. Like transistor density, however, there’s also a limit to how many photo detectors will fit in a given area before undesirable effects start to appear.
Image sensors have come a long way since video camera tubes. In the ’70s, the charge-coupled device (CCD) replaced the cathode ray tube as the dominant video capturing technology. A CCD works by arranging capacitors into an array and biasing them with a small voltage. When a photon hits one of the capacitors, it is converted into an electrical charge which can then be stored as digital information. While there are still specialty CCD sensors for some niche applications, most image sensors are now of the CMOS variety. CMOS uses photodiodes, rather than capacitors, along with a few other transistors for every pixel. CMOS sensors perform better than CCD sensors because each pixel has an amplifier which results in more accurate capturing of data. They are also faster, scale more readily, use fewer components in general, and use less power than a comparably sized CCD. Despite all of these advantages, however, there are still many limitations to modern sensors when more and more of them get packed onto a single piece of silicon.
While transistor density tends to be limited by quantum effects, image sensor density is limited by what is effectively a “noisy” picture. Noise can be introduced in an image as a result of thermal fluctuations within the material, so if the voltage threshold for a single pixel is so low that it falsely registers a photon when it shouldn’t, the image quality will be greatly reduced. This is more noticeable in CCD sensors (one effect is called “blooming“) but similar defects can happen in CMOS sensors as well. There are a few ways to solve these problems, though.
First, the voltage threshold can be raised so that random thermal fluctuations don’t rise above the threshold to trigger the pixels. In a DSLR, this typically means changing the ISO setting of a camera, where a lower ISO setting means more light is required to trigger a pixel, but that random fluctuations are less likely to happen. From a camera designer’s point-of-view, however, a higher voltage generally implies greater power consumption and some speed considerations, so there are some tradeoffs to make in this area.
Another reason that thermal fluctuations cause noise in image sensors is that the pixels themselves are so close together that they influence their neighbors. The answer here seems obvious: simply increase the area of the sensor, make the pixels of the sensor bigger, or both. This is a good solution if you have unlimited area, but in something like a cell phone this isn’t practical. This gets to the core of the reason that most modern cell phones seem to be practically limited somewhere in the sixteen-to-twenty megapixel range. If the pixels are made too small to increase megapixel count, the noise will start to ruin the images. If the pixels are too big, the picture will have a low resolution.
There are some non-technological ways of increasing megapixel count for an image as well. For example, a panoramic image will have a megapixel count much higher than that of the camera that took the picture simply because each part of the panorama has the full mexapixel count. It’s also possible to reduce noise in a single frame of any picture by using lenses that collect more light (lenses with a lower f-number) which allows the photographer to use a lower ISO setting to reduce the camera’s sensitivity.
Gigapixels!
Of course, if you have unlimited area you can make image sensors of virtually any size. There are some extremely large, expensive cameras called gigapixel cameras that can take pictures of unimaginable detail. Their size and cost is a limiting factor for consumer devices, though, and as such are generally used for specialty purposes only. The largest image sensor ever built has a surface of almost five square meters and is the size of a car. The camera will be put to use in 2019 in the Large Synoptic Survey Telescope in South America where it will capture images of the night sky with its 8.4 meter primary mirror. If this was part of the megapixel race in consumer goods, it would certainly be the winner.
With all of this being said, it becomes obvious that there are many more considerations in a digital camera than just the megapixel count. With so many facets of a camera such as physical sensor size, lenses, camera settings, post-processing capabilities, filters, etc., the megapixel number was essentially an easy way for marketers to advertise the claimed superiority of their products until the practical limits of image sensors was reached. Beyond a certain limit, more megapixels doesn’t automatically translate into a better picture. As already mentioned, however, the megapixel count can be important, but there are so many ways to make up for a lower megapixel count if you have to. For example, images with high dynamic range are becoming the norm even in cell phones, which also helps eliminate the need for a flash. Whatever you decide, though, if you want to start taking great pictures don’t worry about specs; just go out and take some photographs!
(Title image: VISTA gigapixel mosaic of the central parts of the Milky Way, produced by European Southern Observatory (ESO) and released under Creative Commons Attribution 4.0 International License. This is a scaled version of the original 108,500 x 81,500, 9-gigapixel image.)
Like a lot of mass-produced consumer goods, it turns out that the internal workings of Bluetooth headphones are the same across a lot of different brands. One common Bluetooth module is the CSR8645, which [lorf] realized was fairly common and (more importantly) fairly easy to modify. [lorf] was able to put together a toolkit to reprogram this Bluetooth module in almost all of these headphones.
This tip comes to us from [Tigox] who has already made good use of [lorf]’s software. Using the toolkit, he was able to reprogram his own Bluetooth headphones over a USB link to his computer. After downloading and running [lorf]’s program, he was able to modify the name of the device and, more importantly, was able to adjust the behavior of the microphone’s gain which allowed him to have a much more pleasant user experience.
Additionally, the new toolkit makes it possible to flash custom ROMs to CSR Bluetooth modules. This opens up all kinds of possibilities, including the potential to use a set of inexpensive headphones for purposes other than listening to music. The button presses and microphones can be re-purposed for virtually any task imaginable. Of course, you may be able to find cheaper Bluetooth devices to repurpose, but if you just need to adjust your headphones’ settings then this hack will be more useful.
[Featured and Thumbnail Image Source by JLab Audio LLC – jlabaudio.com, CC BY-SA 4.0]
There aren’t too many sports named for the sound that is produced during the game. Even though it’s properly referred to as “table tennis” by serious practitioners, ping pong is probably the most obvious. To that end, [Nekojiru] built a ping pong ball juggling robot that used those very acoustics to pinpoint the location of the ball in relation to the robot. Not satisfied with his efforts there, he moved onto a visual solution and built a new juggling rig that uses computer vision instead of sound to keep a ping pong ball aloft.
The main controller is a Raspberry Pi 2 with a Pi camera module attached. After some mishaps with the planned IR vision system, [Nekojiru] decided to use green light to illuminate the ball. He notes that OpenCV probably wouldn’t have worked for him because it’s not fast enough for the 90 fps that’s required to bounce the ping pong ball. After looking at the incoming data from this system, an algorithm extracts 3D information about the ball and directs the paddle to strike the ball in a particular way.
If you’ve ever wanted to get into real-time object tracking, this is a great project to look over. The control system is well polished and the robot itself looks almost professionally made. Maybe it’s possible to build something similar to test [Nekojiru]’s hypothesis that OpenCV isn’t fast enough for this. If you want to get started in that realm of object tracking, there are some great projects that make use of that piece of software as well.
Until the industrial revolution, humans made use of animals to make our labor easier. This is still seen in some niche areas, like how no machine yet has been invented that’s as good at sniffing out truffles as pigs are. [William] has hearkened back to humanity’s earlier roots, but in a more modern twist has made something of a general purpose dog that could feasibly do any work imaginable. Now his dog is remote-controlled.
[William] accomplished the monumental task in a literally cartoonish fashion using the old trope of hanging a hot dog in front of something’s face to get them to chase it. The attachment point was fitted with a remote control receiver and an actuator to get the hanging hot dog to dangle a little bit more to the dog’s right or left, depending on where the “operator” wants the dog to go. [William]’s bulldog seems to be a pretty good sport about everything and isn’t any worse for wear either.
Believe it or not, there has been some actual research done into remote controlling animals, although so far it’s limited to remote-controlled cockroaches. We like the simplicity of the remote-controlled dog, though, but don’t expect to see these rigs replacing leashes anytime soon!
While there’s something to be said for dead-bug construction, hot glue, and other construction methods that simply get the job done, it’s inspiring to see other builds that are refined and intentional but that still hack together things for purposes other than their original intent. To that end, [Li Zanwen] has designed an interesting new lamp that uses magnets to turn itself on in a way that seems like a magnetic switch of sorts, but not like any we’ve ever seen before.
While the lamp does use a magnetic switch, it’s not a traditional switch at all. There are two magnetic balls on this lamp attached by strings. One hangs from the top of the circular lamp and the other is connected to the bottom. When this magnet is brought close to the hanging magnet, the magnetic force is enough to both levitate the lower magnet, and pull down on a switch that’s hidden inside the lamp which turns it on. The frame of the lamp is unique in itself, as the lights are arranged on the inside of the frame to illuminate the floating magnets.
While we don’t typically feature design hacks, it’s good to see interesting takes on common things. After all, you never know what’s going to inspire your next hackathon robot, or your next parts drawer build. All it takes is one spark of inspiration to get your imagination going!
