[Flamingo-tech]’s Xiaomi air purifier has a neat safety feature: it will refuse to run if a filter needs replacement. Of course, by “neat” we mean “annoying”. Especially when the purifier sure seems to judge a filter to be useless much earlier than it should. Is your environment relatively clean, and the filter still has legs? Are you using a secondary pre-filter to extend the actual filter’s life? Tough! Time’s up. Not only is this inefficient, but it’s wasteful.
[Flamingo-tech] has long been a proponent of fooling Xiaomi purifiers into acting differently. In the past, this meant installing a modchip to hijack the DRM process. That’s a classic method of getting around nonsense DRM on things like label printers and dishwashers, but in this case, reverse-engineering efforts paid off.
It’s now possible to create simple NFC stickers that play by all the right rules. Is a filter’s time up according to the NFC sticker, but it’s clearly still good? Just peel that NFC sticker off and slap on a new one, and as far as the purifier is concerned, it’s a new filter!
If you’re interested in the reverse-engineering journey, there’s a GitHub repository with all the data. And for those interested in purchasing compatible NFC stickers, [Flamingo-tech] has some available for sale.
The “razor and blades model” probably set a lot of young hackers on their current trajectory. If we buy a widget, we want to pick our widget refills instead of going back to the manufacturer for their name-brand option. [Flamingo-Tech] was having none of it when they needed a new filter for their Xiaomi air purifier so they set out to fool it into thinking there was a genuine replacement fresh from the box. Unlike a razor handle, the air purifier can refuse to work if it is not happy, so the best option was to make a “mod-chip.”
The manufacturer’s filters have a Near-Field Communication (NFC) chip and antenna which talk to the base station. The controller receives the filter data via I2C, but the mod-chip replaces that transmitter and reassures the controller that everything is peachy in filter town. On top of the obvious hack here, [Flamingo-Tech] shows us how to extend filter life with inexpensive wraps, so that’s a twofer. You can create your own mod-chip from the open-source files or grab one from [Flamingo-Tech’s] Tindie store.
Wireless charging is conceptually simple. Two coils form an ad hoc transformer with the primary in the charger and the secondary in the charging device. However, if you’ve ever had a wireless charging device, you know that reality can be a bit more challenging since the device must be positioned just so on the charger. Xiaomi has a multi-coil charger that can charge multiple devices and is tolerant of their positioning on the charger. How does it work? [Charger Lab] tears one apart and finds 19 coils and a lot of heat management crammed into the device.
The first part of the post is a terse consumer review of the device, looking at its dimensions and features. But the second part is when the cover comes off. The graphite heat shield looks decidedly like an accidental spill of something, but we’re sure that’s just how it appears. The coils are packed in tight in three layers. We have to wonder about their mutual interactions, and we assume that only some of them are active at any given time. The teardown shows a lot of the components and even pulls datasheets on many components, but doesn’t really go into the theory of operation.
Still, this is an unusual device to see from the inside. It is impressive to see so much power and thermal management in such a tiny package. We wonder that we don’t see more wireless charging in do-it-yourself projects. We do see some, of course. Not to mention grafting a charging receiver to an existing cell phone.
If we’ve learned anything over the years, it’s that hackers love to know what the temperature is. Seriously. A stroll through the archives here at Hackaday uncovers an overwhelming number of bespoke gadgets for recording, displaying, and transmitting the current conditions. From outdoor weather stations to an ESP8266 with a DHT11 soldered on, there’s no shortage of prior art should you want to start collecting your own environmental data.
Now obviously we’re big fans of DIY it here, that’s sort of the point of the whole website. But there’s no denying that it can be hard to compete with the economies of scale, especially when dealing with imported goods. Even the most experienced hardware hacker would have trouble building something like the Xiaomi LYWSD03MMC. For as little as $4 USD each, you’ve got a slick energy efficient sensor with an integrated LCD that broadcasts the current temperature and humidity over Bluetooth Low Energy.
It’s pretty much the ideal platform for setting up a whole-house environmental monitoring system except for one detail: it’s designed to work as part of Xiaomi’s home automation system, and not necessarily the hacked-together setups that folks like us have going on at home. But that was before Aaron Christophel got on the case.
Believing that such a well crafted projected deserved a second look, and frankly because I wanted to start monitoring the conditions in my own home on the cheap, I decided to order a pack of Xiaomi thermometers and dive in.
There are millions of IoT devices out there in the wild and though not conventional computers, they can be hacked by alternative methods. From firmware hacks to social engineering, there are tons of ways to break into these little devices. Now, four researchers at the National University of Singapore and one from the University of Maryland have published a new hack to allow audio capture using lidar reflective measurements.
The hack revolves around the fact that audio waves or mechanical waves in a room cause objects inside a room to vibrate slightly. When a lidar device impacts a beam off an object, the accuracy of the receiving system allows for measurement of the slight vibrations cause by the sound in the room. The experiment used human voice transmitted from a simple speaker as well as a sound bar and the surface for reflections were common household items such as a trash can, cardboard box, takeout container, and polypropylene bags. Robot vacuum cleaners will usually be facing such objects on a day to day basis.
The bigger issue is writing the filtering algorithm that is able to extract the relevant information and separate the noise, and this is where the bulk of the research paper is focused (PDF). Current developments in Deep Learning assist in making the hack easier to implement. Commercial lidar is designed for mapping, and therefore optimized for reflecting off of non-reflective surface. This is the opposite of what you want for laser microphone which usually targets a reflective surface like a window to pick up latent vibrations from sound inside of a room.
Deep Learning algorithms are employed to get around this shortfall, identifying speech as well as audio sequences despite the sensor itself being less than ideal, and the team reports achieving an accuracy of 90%. This lidar based spying is even possible when the robot in question is docked since the system can be configured to turn on specific sensors, but the exploit depends on the ability to alter the firmware, something the team accomplished using the Dustcloud exploit which was presented at DEF CON in 2018.
The Xiaomi LYWSD03MMC temperature and humidity sensor is ridiculously cheap. If you’re buying a few at a time, you can expect to pay as little as $5 USD a pop for these handy Bluetooth Low Energy environmental sensors. Unfortunately, that low price tag comes with a bit of a catch: you can only read the data with the official Xiaomi smartphone application or by linking it to one of the company’s smart home hubs. Or at least, that used to be the case.
The new firmware publishes the temperature, humidity, and battery level every minute through a BLE advertisement broadcast. In other words, that means client devices can read data from the sensor without having to be paired. Scraping this data is quite simple, and the GitHub page includes a breakdown of what each byte in the broadcast message means. Avoiding direct connections not only makes it easier to quickly read the values from multiple thermometers, but should keep the device’s CR2032 battery going for longer.
But perhaps the most impressive part of this project is how you get the custom firmware installed. You don’t need to crack the case or solder up a programmer. Just load the flasher page on a computer and browser combo that supports Web Bluetooth (a smartphone is probably the best bet), point it to the MAC address of the thermometer you want to flash, and hit the button. [Aaron] is no stranger to developing user-friendly OTA installers for his firmware projects, but even for him, it’s quite impressive.
Phones used to be phones. Then we got cordless phones which were part phone and part radio. Then we got cell phones. But with smartphones, we have a phone that is both a radio and a computer. Tiny battery operated computers are typically a bit anemic, but as technology marches forward, those tiny computers grew to the point that they outpace desktop machines from a few years ago. That means more and more phones are incorporating technology we used to reserve for desktop computers and servers. Case in point: Xiaomi now has a smartphone that sports a RAM drive. Is this really necessary?
While people like to say you can never be too rich or too thin, memory can never be too big or too fast. Unfortunately, that’s always been a zero-sum game. Fast memory tends to be lower-density while large capacity memory tends to be slower. The fastest common memory is static RAM, but that requires a lot of area on a chip per bit and also consumes a lot of power. That’s why most computers and devices use dynamic RAM for main storage. Since each bit is little more than a capacitor, the density is good and power requirements are reasonable. The downside? Internally, the memory needs a rewrite when read or periodically before the tiny capacitors discharge.
Although dynamic RAM density is high, flash memory still serves as the “disk drive” for most phones. It is dense, cheap, and — unlike RAM — holds data with no power. The downside is the interface to it is cumbersome and relatively slow despite new standards to improve throughput. There’s virtually no way the type of flash memory used in a typical phone will ever match the access speeds you can get with RAM.
So, are our phones held back by the speed of the flash? Are they calling out for a new paradigm that taps the speed of RAM whenever possible? Let’s unpack this issue.