Lifeboat Foundation

A research group led by Prof. Chen Tao at the Ningbo Institute of Materials Technology and Engineering (NIMTE) of the Chinese Academy of Sciences (CAS), developed a novel soft self-healing and adhesive human-machine interactive touch pad based on transparent nanocomposite hydrogels, in cooperation with the researchers from the Beijing Institute of Nanoenergy and Nanosystems of CAS. The study was published in Advanced Materials.

With the rapid development of information technology and the Internet of things, flexible and wearable electronic devices have attracted increasing attention. A touch pad is a requisite input device for a mobile phone, smart appliance and point-of-information terminal. Indium tin oxide (ITO) has been used as the dominant transparent conductive film for manufacturing commercial touch pads, which inevitably have obvious shortcomings, like fragility.

To improve the stretchability and biocompatibility of touch pads to allow their interaction with humans, the researchers at NIMTE developed highly transparent and stretchable polyzwitterion-clay nanocomposite hydrogels with transmittance of 98.8% and fracture strain beyond 1500%.

CSL’s Systems and Networking Research Group (SyNRG) is defining a new sub-area of mobile technology that they call “earable computing.” The team believes that earphones will be the next significant milestone in wearable devices, and that new hardware, software, and apps will all run on this platform.

“The leap from today’s earphones to ‘earables’ would mimic the transformation that we had seen from basic phones to smartphones,” said Romit Roy Choudhury, professor in electrical and computer engineering (ECE). “Today’s smartphones are hardly a calling device anymore, much like how tomorrow’s earables will hardly be a smartphone accessory.”

Instead, the group believes tomorrow’s earphones will continuously sense human behavior, run acoustic augmented reality, have Alexa and Siri whisper just-in-time information, track user motion and health, and offer seamless security, among many other capabilities.

Light-emitting diodes—LEDs—can do way more than illuminate your living room. These light sources are useful microelectronics too.

Smartphones, for example, can use an LED proximity sensor to determine if you’re holding the phone next to your face (in which case the screen turns off). The LED sends a pulse of light toward your face, and a timer in the phone measures how long it takes that light to reflect back to the phone, a proxy for how close the phone is to your face. LEDs are also handy for distance measurement in autofocus cameras and gesture recognition.

One problem with LEDs: It’s tough to make them from silicon. That means LED sensors must be manufactured separately from their device’s silicon-based processing chip, often at a hefty price. But that could one day change, thanks to new research from MIT’s Research Laboratory of Electronics (RLE).

Recently, Google introduced Portrait Light, a feature on its Pixel phones that can be used to enhance portraits by adding an external light source not present at the time the photo was taken. In a new blog post, Google explains how they made this possible.

In their post, engineers at Google Research note that professional photographers discovered long ago that the best way to make people look their best in portraits is by using secondary flash devices that are not attached to the camera. Such flash devices can be situated by the photographer prior to photographing a subject by taking into account the direction their face is pointing, other light available, skin tone and other factors. Google has attempted to capture those factors with its new portrait-enhancing software. The system does not require the camera phone operator to use another light source. Instead, the software simply pretends that there was another light source all along, and then allows the user to determine the most flattering configuration for the subject.

The engineers explain they achieved this feat using two algorithms. The first, which they call automatic directional light placement, places synthetic light into the scene as a professional photographer would. The second algorithm is called synthetic post-capture relighting. It allows for repositioning the light after the fact in a realistic and natural-looking way.

Being able to see, move, and exercise independently is something most of us take for granted. [Thomas Panek] was an avid runner before losing his sight due to a genetic condition, and had to rely on other humans and guide dogs to run again. After challenging attendants at a Google hackathon, Project Guideline was established to give blind runners (or walkers) independence from a cane, dog or another human, while exercising outdoors. Using a smartphone with line following AI software, and bone conduction headphones, users can be guided along a path with a line painted on it. You need to watch the video below to get a taste of just how incredible it is for the users.

Getting a wheeled robot to follow a line is relatively simple, but a running human is by no means a stable sensor platform. At the previously mentioned hackathon, developers put together a rough proof of concept with a smartphone, using its camera to recognize a painted line on the ground and provide left/right audio cues. As the project developed, the smartphone was attached to a waist belt and bone conduction headphones were used, which don’t affect audio situational awareness as much as normal headphones.

The shaking and side to side movement of running, and varying light conditions and visual obstructions in the outdoors made the problem more difficult to solve, but within a year the developers had completed successful running tests with [Thomas] on a well-lit indoor track and an outdoor pedestrian path with a temporary line. For the first time in 25 years, [Thomas] was able to run independently.

:ooooooooooo.

How bright is your flashlight? I only have the one on my phone because I’m completely unprepared for any sort of emergency situation. Well, presumably with the belief that it should be daylight all the time, the team over at Hacksmith Industries took it upon themselves to build a giant, 1,414,224 lumen flashlight. I can already imagine myself staring at it until I go blind.

Continue reading “Team Builds 1.4 Million Lumen ‘World’s Brightest’ Flashlight” »

Ever dream about never having to charge your phone?

Nikola Tesla couldn’t figure out the secret to ubiquitous wireless power. Now, more than 100 years later, are we any closer to pulling it off?

Be it with smartphones, laptops, or mainframes: The transmission, processing, and storage of information is currently based on a single class of material—as it was in the early days of computer science about 60 years ago. A new class of magnetic materials, however, could raise information technology to a new level. Antiferromagnetic insulators enable computing speeds that are a thousand times faster than conventional electronics, with significantly less heating. Components could be packed closer together and logic modules could thus become smaller, which has so far been limited due to the increased heating of current components.

Information transfer at room temperature

So far, the problem has been that the information transfer in antiferromagnetic insulators only worked at low temperatures. But who wants to put their smartphones in the freezer to be able to use it? Physicists at Johannes Gutenberg University Mainz (JGU) have now been able to eliminate this shortcoming, together with experimentalists from the CNRS/Thales lab, the CEA Grenoble, and the National High Field Laboratory in France as well as theorists from the Center for Quantum Spintronics (QuSpin) at the Norwegian University of Science and Technology. “We were able to transmit and process information in a standard antiferromagnetic insulator at room temperature—and to do so over long enough distances to enable information processing to occur”, said JGU scientist Andrew Ross. The researchers used iron oxide (α-Fe₂O₃), the main component of rust, as an antiferromagnetic insulator, because iron oxide is widespread and easy to manufacture.

Powerful neural networks could soon train on smartphones with dramatically faster speeds and less energy.