SummaryResearchers at Caltech have developed a prototype miniature medical device that could ultimately be used in “smart pills” to diagnose and treat diseases. This is critical for the function of biosensors and smart pills. A key to the new technology—and what makes it unique among other microscale medical devices—is that its location can be precisely identified within the body, something that proved challenging before. The picture is about an ATOMS microchip localized within the gastrointestinal tract. bodyCalled ATOMS, which is short for addressable transmitters operated as magnetic spins, the new silicon-chip devices borrow from the principles of magnetic resonance imaging (MRI), in which the location of atoms in a patient's body is determined using magnetic fields. The microdevices would also be located in the body using magnetic fields—but rather than relying on the body's atoms, the chips contain a set of integrated sensors, resonators, and wireless transmission technology that would allow them to mimic the magnetic resonance properties of atoms. The ATOMS device seen next to a penny. The device has a surface area of 1.4 square millimeters, 250 times smaller than a penny. A key principle of MRI is that a magnetic field gradient causes atoms at two different locations to resonate at two different frequencies, making it easy to tell where they are. The researchers wanted to embody this elegant principle in a compact integrated circuit. ATOMS devices also resonate at different frequencies depending on where they are in a magnetic field. The scientists wanted to make this chip very small with low power consumption, and that comes with a lot of engineering challenges. They had to carefully balance the size of the device with how much power it consumes and how well its location can be pinpointed.The devices are still preliminary but could one day serve as miniature robotic wardens of our bodies, monitoring a patient's gastrointestinal tract, blood, or brain. They could measure factors that indicate the health of a patient—such as pH, temperature, pressure, sugar concentrations—and relay that information to doctors. Or, the devices could even be instructed to release drugs. Microscale and Biosensors You could have dozens of microscale devices and biosensors -traveling around the body taking measurements or intervening in disease. These devices can all be identical, but the ATOMS devices would allow you to know where they all are and talk to all of them at once. The researchers compare it to the 1966 sci-fi movie Fantastic Voyage, in which a submarine and its crew are shrunk to microscopic size and injected into the bloodstream of a patient to heal him from the inside—but, instead of sending a single submarine, you could send a flotilla. The researchers say the devices are still preliminary but could one day serve as miniature robotic wardens of our bodies, monitoring a patient's gastrointestinal tract, blood, or brain. The devices could measure factors that indicate the health of a patient—such as pH, temperature, pressure, sugar concentrations—and relay that information to doctors. Or, the devices could even be instructed to release drugs. This chip is totally unique: there are no other chips that operate on these principles. Integrating all of the components together in a very small device while keeping the power low was a big task. The final prototype chip, which was tested and proven to work in mice, has a surface area of 1.4 square millimeters, 250 times smaller than a penny. It contains a magnetic field sensor, integrated antennas, a wireless powering device, and a circuit that adjusts its radio frequency signal based on the magnetic field strength to wirelessly relay the chip’s location. In conventional MRI, all of these features are intrinsically found in atoms. Ther researchers still had to create an architecture that functionally mimics them for our chip. Article from CaltechArticle edit by kynix

SummaryThe invention of electril trucks has bring a lot of benefit for human being. An electric truck is a truck powered by electricity. For information on trucks using a combination of internal combustion engines and electric propulsion, see Hybrid electric truck. Now they are having a moment in the spotlight,however,they still have a long haul cause the costs and other limitations.  Tesla Inc. plans to unveil a semi tractor-trailer this week, its first foray into trucking after more than a decade of making cars and SUVs. German automaker Daimler AG showed off its own electric semi last month and says it could be on sale in a few years. Truck rental company Ryder just added 125 all-electric vans made by California startup Chanje to its fleet. "It's kind of like the checkered flag is being waved," said Glen Kedzie, energy and environmental counsel with the American Trucking Associations. "We've seen different fuels come and go, and electric has gotten to the front of the line." According to the data of Navigant Research, global sales of pure electric trucks are expected to grow exponentially from 4,100 in 2016 to 70,600 in 2026 as battery costs fall and more options enter the market.elivery companies, mail services and utilities will be among the biggest purchasers, and most of the growth will come from Europe, China and the U.S. Most electric trucks on the road will be medium-duty vehicles like delivery vans or garbage trucks. They're quiet and emission-free, and they can be plugged in and charged at the end of a shift. They're ideal for predictable urban routes of 100 miles or less; a longer range than that requires more batteries, which are heavy and expensive. Battery Costs IssueHowever,it's cost that cause a big issue. A medium-duty electric truck costs about $70,000 more than equivalent diesel trucks, according to the consulting firm Deloitte. Buyers considering electrics have to weigh what they can save on fuel and maintenance costs, since electrics have fewer parts.Heavy-duty trucks like electric semis have even further to go before they can be competitive with diesels. Some of those trucks are used for shorter routes, but to achieve a longer range of 300 miles, they require more batteries.  Expensive EletrificationDeloitte estimates electrification adds around $150,000 to the cost of a heavy-duty vehicle, or more than double the cost of some diesel tractor-trailers. Electric semi trucks will have the added problem of long charging times and little highway charging infrastructure."I see it being relevant but not ready for prime time," Chanje CEO Bryan Hansel said of long-haul electric trucks. He thinks it will be five years or more before the battery technology and infrastructure can support cross-country electric trucking. "It's a big prize, but the physics haven't caught up yet," he said. Different ThinkingOther analysts,however,believe that this situation will change. Battery costs are expected to fall significantly over the next decade as technology improves. Deloitte expects battery costs for trucks to fall from $260 per kilowatt-hour in 2016 to $122 in 2026. That would cut the cost of a 300 kWh battery pack—like the one in Daimler's prototype semi —from $78,000 to $36,600. At the same time,regulations will drive interest in electric trucks. In the U.S., trucks must meet stricter emissions standards through 2027 under rules that went into effect last year. China is also tightening emissions standards. And several major cities, including Paris and Mexico City, have called for a ban on diesels by 2025 to improve air quality. Incentives are also enticing companies to add electric trucks to their fleets. Companies that buy or lease vans from Chanje are eligible for an $80,000 voucher per vehicle from the state of California, for example. France pays out 10,000 euros ($11,669) to buyers who replace diesel vehicles with electric ones.  Companies' GoalsCompanies are also experimenting with electrics—and other alternatives, like natural gas—because they want to meet their own sustainability goals and figure out the optimal mix for their fleets. United Parcel Service, for example, has 300 electric trucks in its global fleet of 100,000 vehicles, mostly in the U.S. and Europe, said Scott Phillippi, UPS's Senior Director of Maintenance and Engineering for international operations. Many of UPS's delivery routes require trucks to travel less than 100 miles per day, a range easily met by an electric truck, Phillippi said. He said electric trucks also help the company take advantage of incentives. UPS has set a goal of having 25 percent of its fleet be made up of alternative fuel vehicles by 2020, in part to encourage manufacturers to keep building and improving such trucks. "The proof of concept time is over," he said. "Everybody is starting to agree it's not a matter of if, it's a matter of when." 

SummaryIncreasing demand for energy and power encourages companies operating in energy and power industry to adopt solutions that can help them enhance production output with minimum errors and reduced down-time on a global scale. The products are offered specifically for the energy sector to enhance operations in the energy data management area. Industry 4.0 solutions help power plant owners, operators, and Original Equipment Manufacturers (OEMs) in the power industry make improved business decisions based on performance and operational readiness of their plant equipment.According to the MarketsandMarkets forecast, the Industry 4.0 market in energy and power was valued at $1.30m in 2016 and is expected to reach $3.22bn by 2022, at a CAGR of 16.33% between 2017 and 2022. IoT and Power IndustryIndustry 4.0 is being led by IoT and it plays an important role in condition monitoring and predictive and proscriptive maintenance of assets.Plant operators need to monitor and control the plant more efficiently, and for doing so, the adoption of advanced technologies such as HMI is increasing significantly in the energy and power industry. IoT provides flexibility to accommodate new energy sources, better management of assets and operations, greater reliability and enhanced security.  Big Data to Transform Power IndustryThe energy and power industry has recognised the benefits of big data as it plays a vital role in solving business problems in utility companies.In this vertical, the big data solutions are gaining traction in various processes such as seismic data analysis, smart grid analytics, and data analysis related to production, testing, logging, and many other operations. Each year, smart grids and smart meters generate hundreds of terabytes of data, which include unstructured and semi-structured data. Companies in the energy and power industry have analysed this huge amount of data to get real time access to the situation. Being largely customer-centric, the energy companies are also making a shift toward providing more personalised products and services to their customers. Big data plays an important role in providing trends and patterns by analysing the data, which in turn are useful for product and service upgradation and enhancement. Real Time Monitoring in Battery ManagementReal-time monitoring is a technique that allows you to determine the current state of queues and channels within a queue manager. The information returned is accurate at the moment the command was issued.It can provide frequent information on batteries which can help protect the batteries.Real time monitoring in battery management can help replace manual checks by information available at monitoring systems. Sensor modules collect the voltage and temperature data from the batteries and data is transferred in real time can help supervisors identify issues if any and which will lead to operational efficiency.   Predictive MaintenancePredictive maintenance (PdM) techniques are designed to help determine the condition of in-service equipment in order to predict when maintenance should be performed. This approach promises cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted.It helps in lowering operating and capital costs by facilitating proactive servicing and repair of assets while allowing more efficient use of maintenance personnel and replacement components.It enables companies to accurately diagnose and prevent failures in real time, which is vital in critical infrastructure applications.  Battery failures can prove to be highly expensive in terms of repair costs, in addition to the delay in transporting goods from the resulting downtime. Predictive battery analytics can also help predict battery failures which allows the supervisors to reduce reliability risk and improve uptime.The need for longer battery life, reduced energy consumption, and lower costs will lead companies to provide intelligent solutions. Cognitive Power Electronics SystemsPower electronics systems equipped with intelligence unit can monitor data from sensors and the data can be used to detect faults in the electronic system for real time optimisation of an application.A power converter with monitoring capabilities would be able to detect impedance changes of a battery,enter into a safe state and send information to external systems for further evaluation. Article from MarketsandMarkets Research Private Ltd.Edit by Kynix

TroublesAs the deployment of Industrial IoT systems continues to proliferate,the streams of data transferred to the cloud skyrockets, drastically increasing the cost for cloud computing.  SolutionIn order to meet this trouble, many systems designers are adopting edge computing,in which data processing is done close to the source like sensors in a bid to reduce data transfer,storage and processing costs,plus address a few other concerns over Cloud Computing,in particular security. What is Big DataBig Data is a broad label for the growing amount of data generated by IoT devices and smart systems. For instance, some aircraft engines have more than 5,000 elements that are monitored at relatively high sample rates. Most of the data is transferred to a ground station for the real-time monitoring of the engine and for future R&D work. But this is only part of a growing trend. Most ‘smart’ systems produce vast amounts of data which needs to be processed immediately or be stored for subsequent processing. Huge datacentres are required if you want to store Big Data.Big Data is a broad label for the growing amount of data generated by IoT devices and smart systems. For instance, some aircraft engines have more than 5,000 elements that are monitored at relatively high sample rates. Most of the data is transferred to a ground station for the real-time monitoring of the engine and for future R&D work. But this is only part of a growing trend. Most ‘smart’ systems produce vast amounts of data which needs to be processed immediately or be stored for subsequent processing. Cloud Computing's advantages and disadvantagesCloud Computing has a lot of advantages including cost efficiency (i.e. no need to invest in and maintain your own hardware), scalability, resource availability (for all your users irrespective of their geographic locations), lower latency (as you can specify servers that are closest to the relevant users/customers) and peace of mind in terms of back-ups. There are,however,some disadvantages also. The biggest of which is that no provider can guarantee 100% availability. Data security and privacy are also causes for concern, both on the cloud and for data in transit. Latency can be an issue for Big Data, and doing computationally intensive tasks on the cloud will increase the cost. Of these concerns the last two, in particular, can be negated through edge processing; i.e. performing much of the computationally intensive work near the source data. Benefits here include real-time or near-real-time data processing and reduced network traffic, as you need only transfer the product of the edge processing, thus resulting in lower Cloud Computing costs. Security and privacy can be improved by keeping the sensitive data (a.k.a. Hot Data) within the edge processing environment and only sending less sensitive (Cold) data to the cloud. FPGAs have the edgeThere are technologies that can be used for edge processing applications. These include the use of traditional CPUs (scoring high in terms of flexibility), application-specific processors (e.g. GPUs) and ASICs/SoCs (scoring high on performance). However, it is FPGAs that are slotting into most edge processing applications. Why is this so? Well, let’s consider the requirements. Edge processing needs to be high-performance and in this respect an FPGA can perform several different tasks in parallel. For example, consider executing many non-dependent computations (such as A=B+C, D=E+F and G=H+I). On a CPU, these would have to be performed sequentially, with each sum requiring a few clock cycles. In an FPGA, an array of adders could do the computations in parallel, possibly requiring only a single clock cycle. Power efficiency is essential too, as the end product may well be battery-powered. With an FPGA the function (design) need be the only circuit present, whereas the architecture of a CPU or GPU may not be fully utilized. Also, with an FPGA comes the benefit of reprogrammability. Higher security is afforded too because the edge processing functions are hard wired into the FPGA. It is also possible to encrypt the transaction bus and to even go as far as designing your own processor. ConnectingA prime example of where edge processing is extremely useful, and in which FPGAs can play a significant role, is within an embedded system in which data derived from images needs to be transferred. For example, in the automotive sector Advanced Driver Assistance Systems (ADAS) are under development to make driving safer, easier and more comfortable, and ADAS is regarded as a significant step towards fully autonomous cars. The data processed by an ADAS can be used to notify the driver of problems or to automatically trigger responses such as deceleration, braking and/or the execution of a manoeuvre. The data can also be useful outside the vehicle. Let's discuss the embedded vision system first though by considering an ADAS demo unit that was built for this year's Embedded Vision show in Santa Clara, California. The demo comprised a TySOM-2-7Z100 prototyping board (see figure 1) which includes a Xilinx Zynq XC7Z100 device and a TySOM-FMC-ADAS daughter board to interface with four 960 x 540 pixel cameras. The processing was shared between a dual-core ARM Cortex-A9 processor and FPGA logic (both of which reside within the Zynq device) and began with frame grabbing images from the cameras and applying an edge detection algorithm (‘edge’ here in the sense of physical edges, such as objects, lane markings etc.). This is a computational-intensive task because of the pixel-level computations being applied (i.e. more than 2 million pixels). To perform this task on the ARM CPU a frame rate of only 3 per second could have been realised, whereas in the FPGA 27.5 fps was achieved.This picture is a TySOM-2-7Z100 prototyping board. Mixed technology (like CPU and FPGA) boards are proving very popular for edge processing applications and for connecting with the cloud.  The ARM CPU was mainly used for superimposing detected edges over the initial camera images, colour-space conversions, the formation of a composite image (see main image) and outputting it to an HD buffer. The FPGA and CPU could also work together to recognise and distinguish between obstacles and pedestrians close to the car and to provide lane departure warnings. What goes upSending the processed data to the cloud for further processing and/or storage is then a relatively simple task. Firstly, an AWS account would be created along with an AWS IoT environment. Next, we would configure a Thing (seeing as it is the IoT) and download the public and private keys needed for secure communications with the cloud.The embedded C MQTT standard would be the ideal Software Development Kit (SDK), because it is secure and requires minimal bandwidth. An application would then be prepared to run on the ARM CPU to publish the data onto the cloud. Imagine a scenario,howevber,under which we have data from thousands of vehicles going to the cloud.Analysis of the data could be performed on the cloud and made available for traffic systems or highway maintenance organisations, for example. There may also be instances where data from the cloud feeds into an edge-processing application, in which case applications are also available from AWS. All in all,there are both advantages and disadvantages associated with cloud computing. And many of the disadvantages will be overcome though edge-processing that FPGAs are a particularly suitable activity.  Article provided by Farhad Fallah,an Application Engineer with EDA company AldecArticle edited by Kynix 

SummaryThe robot comes perfectly if they can walk more naturally for humans.However,it's not an easy job for robots and their designers. Walking on two legs is actually a complicated task,requiring several muscles to perform delicate balancing acts.That's why in spite of years of major technological advancements in the field,humanoid robots are still far from being able to get around easily and reliably. Engineers at EPFL's Biorobotics Laboratory are testing new walking algoritms on a plateform called COMAN, short for COmpliant HuMANoid. This 95-cm-tall humanoid is designed specifically for studying walking – which is why it has no head. COMAN was developed under the EU AMARSi project and is being used by several research teams. The EPFL team is looking specifically at the "brains" of the machine. "We developed algorithms that can improve the robot's balance while it's walking," says Hamed Razavi, a researcher scientist at the Biorobotics Lab.  Body One:Climbing Stairs and Opening Doors The algorithms are geared towards three types of realworld applications. The first is carrying out rescue missions in disastrous scenarios. "In environments designed by humans - like a nuclear power plant where there are stairs to climb and doors to open – humanoid robots can get around more easily than robots with wheels," says Razavi. The second is helping with tasks like carrying heavy boxes or moving objects (see box). And the third is creating exoskeletons for the disabled. "Making the robots more stable is just the tip of the iceberg," says Razavi. The next step is refining the algorithms so that the humanoids have a wider range of movement and can overcome obstacles and walk on irregular or sloped surfaces. Two:In Harmony with Symmetries One of COMAN's distinguishing features is its joints,which are integrated with elastic elements that give it greater flexibility when performing different tasks.The EPFL team came up with a novel control algorithm for the robot, based on the existing symmetries in the structure and dynamics of the robot' as well as the mathematical equations representing the robot dynamics. "You could say we're working in harmony with these symmetries rather than against them. As a result, we obtain a more natural and robust walking gait," says Razavi. The control algorithm uses sophisticated computer programs to carefully analyze the date received from the robot – including its position, velocity, joint angles, etc. – and sends appropriate commands to the motors, telling them what to do in order to maintain the robot's balance. "For example, if someone pushes COMAN, for example, our algorithms will calculate exactly where its foot should land in order to counteract the perturbation," says Razavi. Three: Humanoids Helping Humans As part of this project,Jessica Lanini and Hamed Razavi studied how two people carrying an object together are able to walk,turn and speed up in a coordinated manner - without communicating with each other.Their findings,recently published in PLOS ONE,indicate that the two people automatically synchronize their steps, like a quadruped. Now the researchers plan to apply their results to humanoid robots. Lanini explained:"Whether for manufacturing or natural disasters, we need robots that can interact with humans and help us carry heavy objects,but such robots don't exist. That's because, in order to operate safely and effectively, the robots would need to be able to make decisions and respond to unexpected circumstances." But such robots don't exist. The reason is that in order to operate safely and effectively, the robots would need to be able to make decisions and respond to unexpected circumstances." Article provided by  Ecole Polytechnique Federale de Lausanne. 

A while back,MEMS and Sensors Executive Congress that many designers,researchers and industry reoresentatives argued for putting MEMS devices such as accelerometers and microphones, and a wide variety of other sensors in just about everything was held in San Jose,Calif.. We heard about an electric snowboard with traction control, voice-controlled garbage cans, and accelerometers placed on the nose to listen for speech in noisy environments.But sometimes the simplest example is the most memorable. In this case, that was a MEMS accelerometer—like the one in your step-counter—that thwarts car thieves.  "Passive keyless entry (PKE) systems can be made more secure with an inexpensive accelerometer." Lars Reger, chief technology officer for NXP's automotive division said,"PKE systems unlock a car—and allow it to start with a button push—by recognizing when the “key” is close to the car, either right next to it or inside of it. This is convenient for drivers, who don’t have to remove the key from a pocket or purse. But PKEs are ridiculously easy to hack—at least when a car is sitting in a driveway and the owner is at home." This hack which demoed by Swiss researchers in 2011 and still being used by car thieves around the world today,works because most people toss car keys in a basket or on a counter fairly close to their front door—close enough that a thief with a radio outside can pick up signals from the key. An accomplice with another radio stands near the front door of the car to pick up signals from the key and transmit those signals to the car. The system, concluding that the key is nearby, unlocks the car. Earlier this year, researchers pulled off the hack with US $22 worth of gear in a demo at a security conference reported in Wired. The team suggested that changing the timing of the calls and responses from the car and key could address the problem. At the sametime, PKE key holders were advised to keep their car keys in their refrigerators, whose metal exteriors would block the key's signals. NXP put forward another solution--Enter the accelerometer (and, of course, the company is bringing it to market soon, which is why representatives are willing to talk about it). Business development manager Marc Osajda told me that NXP had initially been working on a mechanical switch to turn the radio in the PKE key on and off. Then, after the company merged with Freescale Semiconductor in 2015, engineers at Freescale made the case for using a MEMS device instead, arguing that its lower power consumption made it a good fit for a gadget with an expected battery life of a year or more.    The 50-cent component works on the assumption that if your PKE key has been sitting in one place for a while, you aren’t going anywhere, so it can turn off its radio and the microcontroller that was listening to the car’s radio; it will turn back on as soon as you pick it up. Osajda said that instead of reducing battery life, putting an accelerometer in the PKE key ends up extending battery life, because the accelerometer uses far less power than the parts it is allowing the key to turn off. It's not a easy work. Osajda said "mostly because car keys take a lot more abuse than wrist wearables". He also He pointed out that people frequently drop their keys (sometimes even out of second story windows onto concrete) or toss them into washing machines (not a surprise for keys designed to stay in your pocket). According to Osajda,NXP's MEMS switch is going into production and they will be incorporated into PKE keys from a variety of manufacturers during 2018.