Technology category

Volterman, Your Personal Smart Wallet

With the rapid growth of technology, smartphones and e-payments are replacing cards, cash, and wallets. However, developers are still trying to keep wallets relevant in the 21st century, and Volterman is the newest attempts. Besides WiFi hotspot and power bank, Volterman also provides novel security features to protect your phone and wallet from loss.

Similar to other smart wallets, Volterman has a GPS tracking capability, so you can find it easily in case it lost. Through Bluetooth connectivity, it connects to the smartphone to ensure that you will not forget one of them. An alarm will start ringing to notify you and pick up what you have missed.

The new innovative idea on Volterman is a small built-in camera. It captures everyone trying to open the wallet while “lost mode” is running. The pictures are sent directly to the paired smartphone, meaning that you will know who is using your wallet and where is he. With an embedded SIM card, you are also able to track your wallet via the website.

Volterman’s Embedded System Specification

Inside the wallet, there is a full computing system to do all the stuff. The main components are:

  • CPU: ARM Cortex A9
  • Memory: 512MB RAM, and 32GB ROM
  • SD card: 64GB embedded card
  • Bluetooth: 5.0
  • Camera: 4MP
  • Mobile Network: Worldwide 2G, 3G
  • Wi-Fi: 802.11 BGN, Hotspot
  • GPS: A-GPS, GLONASS
  • Connector: magnetic connecter by Volterman
  • Power Bank: 2000mA, 2600mA, 5000mA, in addition to the capability of wireless charging.
  • Input voltage: 5V, 1A
  • Output voltage: 5V, 500mA

An interesting point is that the purchase price is covering the data charges for the GPS tracking and sending of photos to the Volterman server. According to the makers, Volterman will automatically connect to local networks in 98 countries, but at the moment the exact tariffs from country to country are unclear. However, it is offering up to 3 times cheaper internet cost than the regular price, with an early estimate of around $15 per 1 GB.

The Volterman comes in three different sizes: a small cardholder model $98 with 2,000-mAh power bank, a conventional bifold wallet $135 with 2,600-mAh power bank, or a larger travel size $157 designed to hold more cards, a passport and with a 5,000-mAh power bank.

After reaching more than one million dollars on IndieGoGo, Volterman is now ready for mass production and estimated to start shipping and the first quarter of 2018.

Take a look at the crowdfunding campaign video below:

ICECool – An Intra-Chip Cooling System That Is More Efficient

In the Moore’s Law race to keep improving computer performance, the IT industry has turned upward, stacking chips like nano-sized 3D skyscrapers. But those stacks have their limits, due to overheating. Researchers from IBM have solved this problem by developing an intra-chip cooling system as a contribution to ICECool program research project by the DARPA (Defense Advanced Research Projects Agency).

ICECool - intra-chip cooling system by IBM
ICECool – intra-chip cooling system by IBM

Today, chips are typically cooled by fans which blow air through heatsinks that sit on top of the chips to carry away excess heat. Advanced water-cooling approaches, which are more effective than air-cooling approaches, replace the heatsink with a cold plate that is fixed on the top of the chip.  But this approach requires extra protection and proper insulation of the chip because of the electrical conductivity of water. Neither of these technologies can cool down the chip much efficiently. Here comes the ICECool that cools the chip down from the inside rather than just from the upper surface.

ICECool uses a nonconductive fluid to bring the fluid into the chip. This completely eliminates the need for a barrier between the chip and fluid. It not only delivers a lower device junction temperature, but also reduces system size, weight, and power consumption significantly. The tests performed on the IBM Power 7+ chips demonstrated junction temperature reduction by 25ᵒ C, and chip power usage reduction by 7 percent compared to traditional air cooling. This is clearly a great achievement when the operating cost is much smaller than the conventional cooling technologies.

IBM’s ICECool intra-chip cooling system solves the problem of cooling the 3D “skyscraper” chips by pumping a heat-extracting dielectric fluid right into microscopic gaps, some no thicker than a single strand of hair, between the chips at any level of the stack. Being nonconducting, the dielectric fluid used in ICECool can come into contact with electrical connections without causing any short circuit, so is not limited to one part of a chip or stack. Based on the tests with IBM Power Systems, ICECool technology could reduce the cooling energy for a traditional air-cooled data center by more than 90 percent.

WISP – Re-programmable Microcontroller That Runs On Energy Harvested From Radio Waves

A new research initiative between the University of Washington’s Sensor Lab and the Technical University of Delft in the Netherlands has created a microprocessor that can power itself through stray radio waves and receive programmable updates in the same fashion. While the RISC-derived 16-bit microcontroller CPU is very weak compared to modern standards, it’s much more powerful than any other device that’s powered by ambient energy in the environment with no battery required.

The WISP 5 - Microchips and sensors run from radio wave's energy
The WISP 5 – Microchips and sensors run from radio wave’s energy

This battery-free system is equipped with a sensor and a microchip, which can be powered entirely by radio waves harvested from the air and is up to 10 times faster than similar ambient-powered devices. Best of all, in contrast to similar devices, it can also download executables, allowing it be reprogrammed or upgraded to newer version of firmware whenever needed. This has significant implications for the Internet of Things development and for ambient computing as a whole.

The variety of handheld, portable technology, and wearable gadgets available today is truly amazing. In order to make devices even more compact and thinner, manufacturers typically try to shrink their designs as much as possible. Unfortunately, device size is ultimately limited by the batteries, all of which have a certain capacity before they dry out and must be recharged again. It is a challenge for engineers and designers to balance battery life with function and aesthetics.

The project of radio wave-driven microcontroller is dubbed WISP, or Wireless Identification and Sensing Platform. RFID (CRFID) technology is an example of  WISP. In particular, WISP is capable of being powered passively by converting radio frequencies emitted by conventional RFID (radio frequency identification) readers into electrical power. The project’s latest accomplishment is the addition of Wisent (short for “wirelessly sent”), a faster and more reliable downstream communication-oriented protocol for CRFIDs that can tolerate fluctuations in operating power.

The WISP is constructed out of an open source, open architecture EPC Class 1 Generation 2 RFID tag that incorporates a fully programmable 16-bit microcontroller, in addition to any add-on sensors. It differs from ordinary RFID tags as it is programmable, and can be multi-functional. The team writes in their research paper,

The novelty of Wisent is its ability to change adaptively the frame length sent by the reader, based on the length throttling mechanism, to minimize the transfer times at varying channel conditions. Wisent enables wireless CRFID reprogramming, demonstrating the world’s first wirelessly reprogrammable CRFID.

A New Soundproof Air-Transparent Window

Imagine you have a window that isolates noises and passes only nature sounds like sea waves in addition to fresh air. Seems like it will happen in dreams only, right? Actually, researchers from South Korea, bring this window from dreams to the real.

Soundproofing is difficult and expensive, it usually relies on transferring sound into a medium which absorbs and attenuates it. But this also will stop the airflow. Sang-Hoon Kima and Seong-Hyun Lee have successfully build a new window that allows airflow to pass without sound and noises.

The new design is simple and depends on two acoustic conditions, strong diffraction and negative bulk modulus.

Strong Diffraction

At first, this method makes the sound waves diffused into a customized resonator called diffraction resonator. This resonator maximizes the diffraction impact with its air hole in the center of the body. In addition, the diameter of the hole will control the range of frequencies to restrict. Only waves with a wavelength smaller than the diameter can pass through the hole.

Artificial atoms of diffraction resonators. Diameters of the air holes: 20mm for (a1), (a2), and (a3), and 50mm for (b1), (b2), and (b3). There are three structures: one room for (a1) and (b1), two rooms for (a2) and (b2), and four rooms for (a3) and (b3).

Negative Bulk Modulus

A material’s bulk modulus means its resistance to compression. It is also an important factor in determining the speed at which sound moves through it. So, a material with a negative bulk modulus exponentially attenuates any sound passing through it.

While it is hard to find a solid material having a negative bulk modulus, Kima and Lee have designed a new sound resonance chamber. This chamber consists of two parallel transparent acrylic plastic plates. The efficiency of the double-glazed window is measured by getting the sound into the chamber. To maximize the efficiency, they drilled a hole through each plate. This double-glazing window has also used as a building block to make windows in larger sizes.

Designs of the medium-sound separator. 20mm (left) and 50mm (right). It is composed of the three kinds of artificial atoms which are connected in series and parallel.

There are several applications of this windows, changing the size of the holes makes the windows tunable for certain frequencies. To know more about this research review this paper.

Researchers Developed Low Cost Battery From Graphite Waste

Lithium-ion batteries are flammable and the price of the raw material is increasing. Scientists and engineers have been trying to find out a safe yet efficient alternative to the Lithium-ion technology. The researchers of Empa and ETH Zürich have discovered promising approaches as to how we might produce powerful batteries out of waste graphite and scrap metal.

Kostiantyn Kravchyk and Maksym Kovalenko, the two chief researchers of the Empa’s Laboratory for Thin Films and Photovoltaics, led the research group. Their ambitious goal is to make a battery out of the most common elements in the Earth’s crust – such as graphite or aluminum. These metals offer a high degree of safety, even if the anode is made of pure metal. This also enables the assembly of the batteries in a very simple and inexpensive way.

In typical lithium-ion battery design, the negative electrode or anode is made from graphite. This new design, however, uses graphite as the positive electrode or cathode. In order to make such batteries run, the liquid electrolyte needs to consist of special ions that form a kind of melt and do not crystallize at room temperature. The metal ions move back and forth between the cathode and the anode in this “cold melt”, encased in a thick covering of chloride ions.

Alternatively, large but lightweight and metal-free organic anions could be used. But, this raises some questions which cannot be solved easily – where are these “large” ions supposed to go when the battery is charged? What could be a suited cathode material? In comparison, the cathode of the lithium-ion battery is made of a metal oxide which can easily absorb the small lithium cations during charging. This does not work for such large organic ions.

To solve the problem, Kovalenko’s team came up with a unique and tricky solution: the researchers turned the principle of the lithium-ion battery upside down. In Kovalenko’s battery, the graphite is used as a cathode; i.e., the positive pole. The thick anions are deposited in the intermediate spaces in the graphite. While searching for the “right” graphite, they found that waste graphite produced in steel production (known as kish graphite) works the best as a cathode material. Natural graphite is suitable when it is in the form of coarse flakes and not too finely ground.

Making AI Projects Become Easier With NVIDIA Jetson

Hardware development boards became a key enabler for many of recent hardware projects. Such as Arduino and Raspberry Pi, these boards are great for beginners and hobbyists to kick start and bring ideas to reality.

Artificial Intelligence and machine learning are the technologies of the future. So it is important to know how the process goes, and what type of hardware to use. But with the limited computing capabilities of current boards, developers need a powerful and easy to use tools.

Nvidia provides a good solution with its Jetson boards, which are siblings to NVIDIA’s Drive PX boards for autonomous driving. The first board TX1 was released in November, 2015, and now Nvidia has just released the more powerful and power-efficient Jetson TX2 board.

Image credit: Android central

The TX2 is a complete supercomputer. It is a development tool and a field-ready module to power any AI-based equipment. Developers can use it to build equipment around, and also use it itself to run demos and simulations.

Jetson TX2 comes with NVIDIA’s Pascal™ architecture, which boasts 150 billion transistors built on 16 nanometer FinFET fabrication technology.

Some of technical specifications

  • NVIDIA Parker series Tegra X2: 256-core Pascal GPU and two 64-bit Denver CPU cores paired with four Cortex-A57 CPUs in an HMP configuration
  • 8GB of 128-bit LPDDR4 RAM
  • 32GB eMMC 5.1 onboard storage
  • 802.11b/g/n/ac 2×2 MIMO Wi-Fi
  • Bluetooth 4.1
  • USB 3.0 and USB 2.0
  • Gigabit Ethernet
  • SD card slot for external storage
  • SATA 2.0
  • Complete multi-channel PMIC
  • 400 pin high-speed and low-speed industry standard I/O connector
Nvidia Jetson TX1 and TX2 comparision

TX2 has two performance operating modes: Max-Q and Max-P. Max-Q is the TX2’s energy efficiency mode, at 7.5W, this mode clocks the Parker SoC for efficiency over performance (essentially placing it right before the bend in the power/performance curve) with NVIDIA claiming that this mode offers 2x the energy efficiency of the Jetson TX1. In this mode, TX2 should have similar performance to TX1 in the latter’s max performance mode.

Meanwhile the board’s Max-P mode is its maximum performance mode. In this mode NVIDIA sets the board TDP to 15W, allowing the TX2 to hit higher performance at the cost of some energy efficiency. NVIDIA claims that Max-P offers up to 2x the performance of the Jetson TX1, though as GPU clock speeds aren’t double TX1’s, it’s going to be a bit more sensitive on an application-by-application basis.

Image credit: anandtech

Devices such as robots, drones, 360 cameras, medical, etc., can use Jetson for “edge” machine learning. The ability to process data locally and with limited power is useful when connectivity bandwidth is limited or spotty (like in remote locations), latency is critical (real-time control), or where privacy and security is a concern.

Jetson TX2 is available as a developer kit for $500 at arrow.com. In fact, this kit comes with design guides and documentation, and is pre-flashed with a Linux development environment. It also supports the NVIDIA Jetpack SDK, which includes the BSP, libraries for deep learning, computer vision, GPU computing, multimedia processing, and more.

Finally, this video compares Jetson TX1 and TX2 boards:

Thin, flexible cooling device

Researchers Developed New Efficient, Thin, and Flexible Cooling Device

Engineers and scientists from the UCLA Henry Samueli School of Engineering and Applied Science and SRI International, California, have created a thin flexible device that could keep smartphones and laptop computers cool and prevent overheating. The component is based on the electrocaloric effect – a phenomenon where the temperature of material changes when an electric field is applied to it. The research has been published in Science.

Thin, flexible cooling device
Thin, flexible cooling device

The system’s flexibility also allows it to be used in wearable electronics, robotic systems, and new types of personalized cooling systems. It is the first demonstration of a solid-state cooling device based on the electrocaloric effect. The method devised by UCLA and SRI researchers is very energy-efficient. It uses a thin polymer film that transfers heat from the heat source – a battery or a processor – to a heat sink, and alternates contact between the two by switching on and off the electric voltage.

Because the polymer film is very flexible, the system can be used in devices with complex shapes or moving surfaces. Body tracking wearable devices can easily accommodate this flexible cooling device. Such cooling pad could keep a person comfortable in a hot office and thus lower the electricity consumption for air conditioning. Or it could be placed in a shoe to keep a runner comfortable while running in the sun. It’s like a personal air conditioner.

The tendency of flexible electronics to overheat remains a major challenge for engineers. The cooling systems in larger devices like air conditioners and refrigerators, which use vapor compression, are just too large for mobile electronics. The new cooling device produces a specific cooling power of 2.8 watts per gram and a COP of 13. This is more efficient and compact than the existing surface-mountable solid-state cooling technologies, opening a path to using the technology for a variety of practical applications.

Roy Kornbluh, an SRI research engineer, said,

The development of practical efficient cooling systems that do not use chemical coolants that are potent greenhouse gases is becoming even more important as developing nations increase their use of air conditioning.

loihi - Intel's self-learning chip

Intel Introduces Loihi – A Self Learning Processor That Mimics Brain Functions

Intel has developed a first-of-its-kind self-learning neuromorphic chip – codenamed Loihi. It mimics the animal brain functions by learning to operate based on various modes of feedback from the environment. Unlike convolutional neural network (CNN) and other deep learning processors, Intel’s Loihi uses an asynchronous spiking model to mimic neuron and synapse behavior in a much closer analog to animal brain behavior.

loihi - Intel's self-learning chip
Loihi – Intel’s self-learning chip

Machine learning models based on CNN use large training sets to set up recognition of objects and events. This extremely energy-efficient chip, which uses the data to learn and make inferences, gets smarter over time and does not need to be trained in the traditional way. The Loihi chip includes digital circuits that mimic the brain’s basic mechanics, making machine learning faster and more efficient while requiring much lower computing power.

The chip offers highly flexible on-chip learning and combines training and inference on a single chip. This allows machines to be autonomous and to adapt in real time instead of waiting for the next update from the cloud. Compared to convolutional neural networks and deep learning neural networks, the Loihi test chip uses many fewer resources on the same task. Researchers have demonstrated learning at a rate that is a 1 million times improvement compared with other typical neural network devices.

The self-learning capabilities prototyped by this test chip have huge potential to improve automotive and industrial applications as well as personal robotics – any application that would benefit from the autonomous operation and continuous learning in an unstructured environment. For example, recognizing the movement of a car or bike for an autonomous vehicle. More importantly, it is up to 1,000 times more energy-efficient than general purpose computing.

Features

  • Fully asynchronous neuromorphic many core mesh.
  • Each neuron capable of communicating with thousands of other neurons.
  • Each neuromorphic core includes a learning engine that can be programmed to adapt network parameters during operation.
  • Fabrication on Intel’s 14 nm process technology.
  • A total of 130,000 neurons and 130 million synapses.
  • Development and testing of several algorithms with high algorithmic efficiency for problems including path planning, constraint satisfaction, sparse coding, dictionary learning, and dynamic pattern learning and adaptation.

vision processing

Role Of Vision Processing With Artificial Neural Networks In Autonomous Driving

In next 10 years, the automotive industry will bring more change than we have seen in the last 50, due to technological advancement. One of the largest changes will be the move to autonomous vehicles, usually known as the self-driving car. Scientists from many universities are striving to implement vision processing with the artificial neural network to provide driver assistance in self-driving cars.

vision processing
Vision processing using convolutional artificial neural networks

Vision processing, as well as artificial neural networks, have been around for many years. Convolutional artificial neural networks (CNN) are sets of algorithms that extract meaningful information from sensor input. CNN’s are very computationally efficient at analyzing a scene. They are also able to identify objects as cars, people, animals, road signs, road junctions, road marking etc. enabling them to determine the relevant reality of the scene. As this system runs in real-time, the decision can be made as soon as the sensing part is complete.

One of the major steps in visual environment understanding for automotive applications is key points tracking and estimating ego-motion and environment structure subsequently from the trajectories of these key points. A propagation based tracking (PBT) method is popularly used to obtain the 2D trajectories from a sequence of images in a monocular camera setup.

The inputs from one or all of the sensors like LIDAR, RADAR, camera, IR, etc. are evaluated and decisions are taken accordingly. For example, if a car in the front suddenly brakes, the onboard computer would instantly verify the distance and calculate the speed with help of the existing sensors. Then it would apply the brakes faster than any human would be able to do. This method helps to prevent an accident with 90% efficiency.

The use of vision processing with CNN is rapidly increasing in automotive applications to enable camera-based autonomous driving. This technology sets a new driving standard. With this technology in our hand, fewer accidents, fewer fatalities, and less pollution are experienced. Vision processing in autonomous driving also enables efficient journeys, reduced crowding, car sharing, and packing cars in more tightly via vehicle to vehicle communication.

hybrid 3d printing

Researchers Developed Hybrid 3D Printing Method To Make Flexible Wearable Devices

Wearable electronic devices that intend to track and measure the body’s movements must be soft enough to flex and stretch to accommodate every body-movement. But, integrating rigid electronics on skin-like flexible materials has proven to be challenging. Clearly, Such components cannot stretch like soft materials can, and this mismatch frequently causes wearable devices to fail. Recently scientists solved this problem by developing a new method called hybrid 3D printing.

Making wearble devices using Hybrid 3D Printing method
Making wearable devices using Hybrid 3D Printing method

A collaboration between the Wyss Institute, Harvard’s John A. Paulson School of Engineering and Applied Sciences, and the Air Force Research Laboratory, has resulted in developing hybrid 3D printing method. It combines soft, electrically conductive inks, and matrix materials with rigid electronics into a uniformly stretchable device. Alex Valentine, a Staff Engineer at the Wyss Institute says,

With this technique, we can print the electronic sensor directly onto the material, digitally pick-and-place electronic components, and print the conductive interconnects that complete the electronic circuitry required to ‘read’ the sensor’s data signal in one fell swoop.

To make the circuits and the flexible layers, the researchers use thermoplastic polyurethane (TPU), both pure and with silver flakes. The method is quite easy to understand. As both the substrate and the electrodes contain TPU, they firmly adhere to one another while they are co-printed layer-by-layer. After the solvent evaporates completely, both of the inks harden, forming an integrated system that is both flexible and stretchable.

As the ink and substrate are 3D-printed, the scientists have complete control over where and how the conductive features are patterned. Thus they can design circuits to create soft electronic devices of nearly every size and shape. The hybrid 3D printing method enables development of flexible, durable wearable devices that move with the body.

A ring that is made using flexible conductingmaterial
A ring that is made using flexible conducting materials

Conductive materials exhibit changes in their electrical conductivity when stretched. Soft sensors, that detect movements, are made of those materials and are coupled with a programmable microcontroller to process those data. The microcontroller also transmits the data to communicate in a human-understandable way. As a proof-of-concept, the team created two devices – a wearable device that indicates how much the wearer’s arm is bending and a pressure sensor in the shape of a person’s left foot.

Watch the video to know about them,