July/August 2014 european www.electronics-eetimes.com business press Augmented reality gets physical with haptics Executive interview: FREE mCube’s CEO Ben Lee SHIPPING ON ORDERS Design Focus: Data Encryption & Security OVER €65! DIGIKEY.COM/ EUROPE 020212_FRSH_EET_EU_Snipe.indd 1 2/2/12 12:37 PM 140129_TOPB_EET_EU.indd 1 1/27/14 11:33 AM JULY/AUGUST 2014 opinion DESIGN & PRODUCTS 4 Will sensor fusion drive neuromorphic computing? SPECIAL FOCUSES: - GEOLOCATION & NAVIGATION 50 Rousset judgment is economic and social mistake 25 Enabling sub-10cm positioning accuracy news & TECHNOLOGY Impulse Response Ultra Wideband (IR- UWB) comes to the rescue for indoor 6 Clearing away the fog of computing for IoT navigation. Intel is bringing its expertise from silicon manufacturing to the Internet 27 Hold back your high tech marketing tactics! of Things with two new ‘Ignition’ Labs in Europe. 28 LEDs tap indoor location technology for social shopping 7 Infineon to create 200 new jobs in Austria 8 Augmented reality gets physical with haptics If all of us are familiar with the - INDUSTRIAL COMPUTING basic silent-mode of most mobile phones, a crude form of haptics, 30 A duel of Atoms: Qseven vs COM Express Mini there is much more to come on When Intel launched the first generation of the Atom the display side. processor Z500 series (codenamed Silverthorne), this represented a major step forward in terms of multimedia 14 E-car research project sets efficiency standards features in compact and mobile applications with an X86 architecture. 15 Can rust really revolutionize solar cell technology? Researchers at Swiss Materials Science and Technology Institu- - DATA ENCRYPTION & SECURITY tion – Empa - have developed a photoelectrochemical cell that 34 Hacking airliners: lessons learned in firmware imitates plant photosynthesis. integrity assurance In April 2013, a security consultant made headlines 16 Iconic Insights: in conversation with Hanns Windele when he claimed he could use an Android smartphone Based in Israel, Inuitive is a natural user to hack in and commandeer commercial jets. interface semiconductor start-up created by communications entrepreneur Shlomo 36 Securing cryptographic assets for Gadot. Hanns Windele of Mentor the Internet of Things Graphics finds out what the future holds A review of various white box for the gesture interpretation market. cryptography techniques for protecting critical cryptographic 18 5G, IoT pose new challenges to testing operations and data in an Jonathan Borrill, Director of Market Strategy at RF environment where white-box attacks are available. test technology provider Anritsu gives us a glimpse of what the hot issues are. 38 Software is the new asset to protect in modern manufacturing 19 Crunch the IoT data before it clogs your network 40 Ethereal encryption: Key management in the Cloud 21 China, not Apple, is way to go, says mCube CEO Ben Lee, CEO of MEMS startup mCube, explains why he wants to 46 READER OFFER spend $37 million on being a supplier of sensors to Chinese ODMs and This month, Altium Ltd is offering EETimes Europe’s avoiding a design win with Apple or readers the chance to win one Samsung. TASKING VX-Toolset for ARM Cortex-M Premium Edition, 22 Xilinx’ SDNet: where software defined networks normally licensed for 2.395 Euros. truly begin 23 Red phosphors enhance white-emitting LEDs 49 distriBUTION CORNER 24 Websites’ emotional impact 51 WHITEPAPERS revealed by webcams 3 Electronic Engineering Times Europe July/August 2014 www.electronics-eetimes.com Will sensor fusion drive neuromorphic computing? By Peter Clarke Sensor fusion is the technique of combining data from are highly parallel and matched to graphics rendering. We are several sensors for improved performance and is one of the starting to see the emergence of computer vision processors latest hot topics in mobile computing partly as a result of large that can be optimized to extract useful information from image numbers of sensors coming on board. sensor data. This could be object detection and recognition, What sensor fusion can do is turn data from what may gesture and facial recognition and increasingly it is being found become hundreds of sensors to useful information for the ap- that the most energy efficient way to perform these tasks are plication processor to use, such as power up the modem and with computing architectures with similarities to neuromorphic graphics as the user has likely picked up the phone – or turn systems. We are seeing CMOS image sensors move towards up the screen brightness because the user has probably gone the hyperspectral to try and extract more information, such as outside. distance or depth information, at the pixel level. Contrast that with neural Finally the adoption of sensor networking, which was a hot fusion in mobile phones is edu- topic 25 years ago as software cating developers to think along simulations of weighted sum- neuromorphic lines. This means a ming networks started to show temperature sensor can be used some interesting abilities to learn to help calibrate a pressure sen- how to process data. However, sor which in turn can help provide hardware integration was less information to inertial sensors. In successful as the number of the end the accuracy of the multi- neurons was relatively limited sensor cross calibrated system is and interfacing to conventional greater than that of the individual computing was a burden. sensors. I predict that neural networks A follow–on from that might – or neuromorphic computing as be to develop architectures of the topic is now called – is about variable resolution. There is no to go through a renaissance and point in wasting energy calculat- could be encouraged by sensor ing values to 32-bit accuracy fusion acting as a pioneer. throughout multiple processors if A first part of the landscape you only want a go/no-go deci- behind this conclusion is that the sion about whether to power-up complexity of conventional digital the LTE modem. circuits with multiple software- And so it should come as programmable cores has reached no surprise that Qualcomm is a level that it is becoming almost working on neuromorphic cores impossible for human developers for potential inclusion in future to understand all the use cases Snapdragon-like application and software paths through the “Neural networks are about to go through a processors. Qualcomm is system and develop tests for renaissance and could be encouraged by sensor developing something called the them. Even though a building Zeroth processor that comprises block approach is taken to make fusion acting as a pioneer” a spiking neural network because use of previously tested sub- of its energy efficiency for systems to try and curtail this exponentially growing problem, encoding information. the fact remains that many companies are now betting their Qualcomm thinks of mobile phone as brain covered in existence on products they cannot be absolutely sure will not sensors including pressure, touch, vision, hearing, humidity. It enter some sort of deadlock condition under some unforeseen envisions a neural processor core able to live side-by-side with set of conditions. conventional software-programmable cores in future application What is really needed is a system that while not perfectly processors. In this way it is possible to develop programs using tested is fit for purpose the vast majority of the time and has the traditional programming languages, but also to lean on the neu- ability to learn and adapt to the time it is not. Does this sound romorphic processor to train the device for human interaction like a neural network? and behaviour. A second part of the landscape is that as more specialized This holds out the promise of not only energy-efficient application-specific processors become economically viable learned behaviour but also a human-machine interface that is because of the size of markets they can serve, their architec- human-friendly. So as sensors proliferate – both on the mobile ture is moving away from general-purpose architectures and phone and in Internet of Things applications – I expect neuro- towards neuromorphics ones. For example graphics processors morphic computing to follow. 4 Electronic Engineering Times Europe July/August 2014 www.electronics-eetimes.com Clearing away the fog of computing for the Internet of Things By Nick Flaherty INTEL IS BRINGING ITS expertise from silicon manufacturing strong engineering expertise.” to the Internet of Things with two new ‘Ignition’ Labs in Europe One areas of focus is the gateway, using processors such to drive the development of IoT systems with a specific focus as Atom and the lower power Quark, to control the interface to on the Internet of Things for smart cities. The labs – in Swindon, sensor networks. This is particularly important for connecting UK and Munich, Germany – follow the first two in Istanbul and legacy systems securely to the Internet, she says, and is part of Stockholm last year. the move to ‘fog computing’ with The labs bring together the whole more intelligence at the edge of eco-system of developers, from the network. hardware to software and services, “Intel believes the numbers are in one room to create a complete, growing exponentially and when interoperable solution over the you are in the billions of devices space of several weeks. range what you really want to This was a lesson learned from do is have the data where it is Intel’s silicon manufacturing exper- needed to make the decision – tise, and particularly from Doug Da- the edge provides the ability to vies who was previously the general make the decision where they are manager of the Intel’s Arizona fab needed.” before taking over as general man- She points to a recent proj- ager of the IoT group at Intel. ect for smart toilets in Heathrow “What we learnt from our fabs Airport’s newly re-developed was that when something goes Terminal 2 in London, which uses wrong, they don’t have a meeting a week for a month, they pull boards and middleware from partner Eurotech, as an example people off the line and put them in a room until its solved,” said of fog computing.