Wirelessly charge a smartphone with a laser

Although mobile devices such as tablets and smartphones let us communicate, work and access information wirelessly, their batteries must still be charged by plugging them in to an outlet. But engineers at the University of Washington have for the first time developed a method to safely charge a smartphone wirelessly using a laser.

As the team reports in a paper published online in the Proceedings of the Association for Computing Machinery on Interactive, Mobile, Wearable & Ubiquitous Technologies, a narrow, invisible beam from a laser emitter can deliver charge to a smartphone sitting across a room – and can potentially charge a smartphone as quickly as a standard USB cable. To accomplish this, the team mounted a thin power cell to the back of a smartphone, which charges the smartphone using power from the laser. In addition, the team custom-designed safety features – including a metal, flat-plate heatsink on the smartphone to dissipate excess heat from the laser, as well as a reflector-based mechanism to shut off the laser if a person tries to move in the charging beam’s path.

The charging beam is generated by a laser emitter that the team configured to produce a focused beam in the near-infrared spectrum. The safety system that shuts off the charging beam centers on low-power, harmless laser “guard beams,” which are emitted by another laser source co-located with the charging laser-beam and physically “surround” the charging beam. Custom 3-D printed “retroreflectors” placed around the power cell on the smartphone reflect the guard beams back to photodiodes on the laser emitter. The guard beams deliver no charge to the phone themselves, but their reflection from the smartphone back to the emitter allows them to serve as a “sensor” for when a person will move in the path of the guard beam. The researchers designed the laser emitter to terminate the charging beam when any object – such as part of a person’s body – comes into contact with one of the guard beams. The blocking of the guard beams can be sensed quickly enough to detect the fastest motions of the human body, based on decades of physiological studies.

The next generation of nano-scale optical devices are expected to operate with Gigahertz frequency, which could reduce the shutter’s response time to nanoseconds.

The beam charges the smartphone via a power cell mounted on the back of the phone. A narrow beam can deliver a steady 2W of power to 15 square-inch area from a distance of up to 4.3 meters, or about 14 feet. But the emitter can be modified to expand the charging beam’s radius to an area of up to 100 square centimeters from a distance of 12 meters, or nearly 40 feet. This extension means that the emitter could be aimed at a wider charging surface, such as a counter or tabletop, and charge a smartphone placed anywhere on that surface.

The researchers programmed the smartphone to signal its location by emitting high-frequency acoustic “chirps.” These are inaudible to our ears, but sensitive enough for small microphones on the laser emitter to pick up.

When the emitter detects the smartphone on the desired charging surface, it switches on the laser to begin charging the battery.

To ensure that the charging beam does not overheat the smartphone, the team also placed thin aluminum strips on the back of the smartphone around the power cell. These strips act as a heatsink, dissipating excess heat from the charging beam and allowing the laser to charge the smartphone for hours. They even harvested a small amount of this heat to help charge the smartphone – by mounting a nearly-flat thermoelectric generator above the heatsink strips.

The researchers believe that their robust safety and heat-dissipation features could enable wireless, laser-based charging of other devices, such as cameras, tablets and even desktop computers. If so, the pre-bedtime task of plugging in your smartphone, tablet or laptop may someday be replaced with a simpler ritual: placing it on a table.

Mind reading equipment almost a reality

It may sound like sci-fy, but mind reading equipment are much closer to become a reality than most people can imagine. A new study carried out at D’Or Institute for Research and Education used a Magnetic Resonance machine (MR) to read participants’ minds and find out what song they were listening to. The study, published today in Scientific Reports, contributes for the improvement of the technique and pave the way to new research on reconstruction of auditory imagination and inner speech. In the clinical domain, it can enhance brain-computer interfaces in order to establish communication with locked-in syndrome patients.

In the experiment, six volunteers heard 40 pieces of classical music, rock, pop, jazz, and others. The neural fingerprint of each song on participants’ brain was captured by the MR machine while a computer was learning to identify the brain patterns elicited by each musical piece. Musical features such as tonality, dynamics, rhythm and timbre were taken in account by the computer.

After that, researchers expected that the computer would be able to do the opposite way: identify which song participants were listening to, based on their brain activity – a technique known as brain decoding. When confronted with two options, the computer showed up to 85% accuracy in identifying the correct song, which is a great performance, comparing to previous studies.

Researchers then pushed the test even harder by providing not two but 10 options (e.g. one correct and nine wrong) to the computer. In this scenario, the computer correctly identified the song in 74% of the decisions.

In the future, studies on brain decoding and machine learning will create possibilities of communication regardless any kind of written or spoken language.

Statue of Peter the Great in St. Petersburg

Algorithm uses Instagram posts to advise tourists

Programmers from ITMO University created a computer algorithm that allows tourists to find places of interest that are most popular with locals based on their instagram posts. To test the algorithm, the team analyzed Instagram photos taken in Saint Petersburg and compiled a list of museums, cafes, streets, and event venues preferred by the residents of Russia’s northern capital, thus providing local suggestions to tourists.

People tend to photograph memorable moments or places. Therefore, social networks, such as Instagram, are constantly becoming more and more popular. There are more than 700 million active Instagram users around the world. In most cases, people post photos either because it’s their first time visiting a place or, on the contrary, because they go there often.

Programmers at the eScience Research Institute at ITMO University found a way to distinguish between Instagram users living in a city and visiting tourists based on how they post on social media. In a nutshell, the researchers discovered which locations were most loved by St. Petersburg residents.

To remove tourists’ input from the analysis, the scientists chose two months of the year with the least number of visitors, that is, February and November, and collected all the posts from Instagram taken during that time in St. Petersburg. Based on each photograph that was posted, the programmers then analyzed the profiles of all the users who posted them.

Tourists would usually post a bunch of pictures made in the center of the city, along the main street, while geotags of residents’ photos were scattered throughout St. Petersburg.

In order to detect city residents more effectively, the scientists used official tourist statistics. According to the information from the city administration, the largest number of tourists comes from the European Union (32%) and their holidays usually do not exceed two weeks. Thus, a user was identified as a tourist if his or her posts in St. Petersburg during a calendar year were covered by two 15-day or less long windows with a gap of at least 30 days between each time period. Furthermore, the programmers excluded the 15 top tourist locations.

The scientists also note that the algorithm now automatically organizes popular locations according to five categories: theaters and museums, restaurants and bars, bridges and streets, parks and other. Thus, the most popular place in the “Theaters and Museums” category was the Ice Palace, a big arena and concert venue, which was more popular than even the world-famous Mariinsky Theater in terms of the number of photographs taken there. In the category “Streets and Bridges”, the locals mostly liked the Alexander Column at the Palace Square and the Fontanka river embankment.

The results of the research were presented at The International Conference on Computational Science and published in Procedia Computer Science.

Statue of Peter the Great in St. Petersburg

Statue of Peter the Great in St. Petersburg

Hristijan Gjoreski / University of Sussex

Smartwatches that learn your every move

Scientists at the University of Sussex have invented a new algorithm that enables smartwatches to detect and record your every move, without being told beforehand what to look for.

Current smartwatches can recognise a limited number of particular activities, including yoga and running, but these are programmed in advance.

This new method enables the technology to discover activities as they happen, not just simply when exercising, but also when brushing your teeth or cutting vegetables.

The algorithm can even track sedentary activity, for instance whether you are lying or sitting down.

Atlas, The Next Generation

A new version of Atlas, designed to operate outdoors and inside buildings. It is specialized for mobile manipulation. It is electrically powered and hydraulically actuated. It uses sensors in its body and legs to balance and LIDAR and stereo sensors in its head to avoid obstacles, assess the terrain, help with navigation and manipulate objects. This version of Atlas is about 5′ 9″ tall (about a head shorter than the DRC Atlas) and weighs 180 lbs.