Friday, March 24, 2017

Medical IoT developer licenses 86 Siemens patents for self-healing networks

By Nick Flaherty

Nexeon MedSystems in the US has licensed a portfolio of IoT patents from Marathon Patent Group. The portfolio of 86 patents originated from Siemens and covers the interconnection via the internet of computing devices embedded in everyday objects, enabling them to send and receive data. The technology can be used in a variety of medical device applications, most notably in hospitals, nursing facilities, or patients' homes.

"The data gathered in these IoT systems can be utilized to help improve the programming for implantable devices," said Nexeon Chairman and CEO Will Rosellini. "An average patient with a chronic disease typically takes more than five different medications everyday, most of which need to be taken at different times of the day and have specific dietary recommendations to accompany the dosages. This same patient is typically demonstrating symptoms associated with cognitive, psychiatric, and motor disorders as well. The promise of keeping the device in the right therapeutic range with data from the IoT is extraordinary."

The portfolio covers self-healing control networks for building automation systems in the hospital and the home. The patents are relevant to wireless mesh networks for use in the IoT and enable simple commissioning, application level security, simplified bridging, and end-to-end IP security.

There is a growing trend in electrophysiology toward remote home-monitoring of implantable cardioverter defibrillators (ICDs), cardiac resynchronization therapy (CRT) devices, pacemakers, and implantable cardiac monitors (ICMs). Nexeon has engaged consultants Battelle to define the data structures and cybersecurity protocols needed to provide the framework for deep learning.

"Siemens is one of the most innovative firms in the world," said Rosellini. "Integrating their network innovation with our patient-specific solutions will substantially reduce the burden of chronic disease. By addressing this unmet need, we will create tremendous value in the form of better, faster care with fewer in-office visits required, easier access to more accurate patient information, and decreased complications and undesired side effects due to more precise therapy and better monitoring."

Related stories: 

Another startup aims for embedded AI

By Nick Flaherty

A spinout from the University of Michigan has raised $9m to develop 'AI-on-a-chip' in a further demonstration of the move of artificial intelligence into the Internet of Things. The move comes just days after ARM and Xilinx announced strategies fo emebdded AI and other startups such as Imagimob and Graphcore are targetting embedded chips.

The company, previously called Isocline, relied on grants and angel investors to develop the underlying technology for its platform and the funding aims to build up the engineering team to develop the chip and software.

At a time when data connections are still unreliable and constrained and even children's toys are getting hacked, it is increasingly important to untether the AI in these devices from the cloud to make them more secure, responsive, seamless, and easily integrated. Because Mythic's local AI platform is untethered and inherently more private, device makers, security platform, and monitoring companies see it as being transformative for their products.

Mythic was born out of the Michigan Integrated Circuits Lab at the University of Michigan in 2012 – a lab known for its world-class low power chip design and multiple venture-backed spin-outs. Co-founders Mike Henry and Dave Fick developed a new deep learning deployment (or inference) model – based on hybrid digital/analog computation– that eliminates costly processors and transfers the deep learning computations to the memory structures storing the algorithm parameters – all while extending battery life by 50x. This design allows the company to essentially put desktop GPU compute capabilities onto a module the size of a shirt button and data-center compute capabilities onto a card-deck sized platform– offering a new level of trust and security to the growing number of smart devices on the market today.

"Other local AI solutions compromise on what consumers and commercial companies care about – battery life, throughput, and accuracy," said Michael Henry, co-founder and CEO of Mythic. "We saw early on the opportunities afforded AI from processor-in-memory technology and new methods of computing outside of the binary 1 and 0 world. This would become a foundation for the Mythic platform that revolutionizes local AI design and performance."

Markets that Mythic will be targeting initially include smart home, action cameras, sophisticated healthcare systems, security and monitoring for commercial and home use and drones for industrial applications. Down the road, Mythic sees interesting use cases for robotics, autonomous vehicles, AR, and VR.

"Mythic is pushing the performance boundaries of local AI so any device can become a true universal assistant," said Steve Jurvetson, Partner at DFJ. "The way local AI is being engineered today is equivalent to trying to make a propeller plane fly faster by stripping down cargo, or adding 18 propellers – working with technology that stalled just doesn't make sense. Just as jet design put flight on a new trajectory, Mythic is doing the same for local AI."

The company is forming engagements with early-adopter customers to field test the technology, with volume shipments projected for mid-2018. The funding round was led by DFJ and includes Lux Capital, Data Collective, and AME Cloud Ventures. 

Wednesday, March 22, 2017

Cloud API for IoT gateways and IoT edge servers simplifies IoT networks

By Nick Flaherty

German embedded board maker congatec has developed a new cloud API to simplify the development of networks across the Internet of things (IoT).

The Cloud API for IoT Gateways highlights the need for equipment suppliers to move up the value chain into the cloud. The API communicates with local smart sensors, processes and converts the acquired data and executes automated actions based on a local rule engine, reducing traffic to the IoT cloud and enabling fast local actions. 
Secure bidirectional data exchange with any suitable clouds is achieved by using the TLS secured MQTT protocol with a design solution using the Microsoft Azure cloud. Clients can access this cloud via https in client or administrator mode. All these features make the Cloud API for IoT Gateways a simple starting point for OEMs that need to access smart sensor networks via IoT gateways and IoT edge servers. Typical application areas can be found in various IoT segments, from industrial production and machinery to smart cities, smart facilities, smart homes, smart energy grids, medical IoT, the transportation sector and digital signage.

The API integrates a broad range of wireless sensor interconnects, including Bluetooth LE, ZigBee, LoRa and other LPWANs, as well as wired protocols for building or factory automation. Even heterogeneous protocol configurations and communication with other gateways are possible.

"Each smart sensor network has its own demands. Often, heterogeneous sensor networks are required and various different database implementations can be found in IoT clouds as well," said said Christian Eder, director of marketing at congatec. "At the edge of the IoT we are able to manage these heterogeneous, bidirectional demands by centrally orchestrating local smart sensor networks including the IoT edge gateways themselves. Our application ready congatec Cloud API for IoT Gateways meets this demand. Its freely programmable software modules can be instantly utilized to get access to our boards and their data as well as connected sensor networks. They are available in C++ and can be used as a blueprint for any custom specific implementations. which highly simplifies the development of individual IoT solutions." 

The main software components are the different Cloud API function modules as well as the demo and test modules for provider independent IoT clouds. The sensor engine of the Cloud API for IoT Gateways makes the communication with the local sensor and actuators independent from any protocol. Additionally, it normalizes the data records to freely definable physical units and checks for consistency. 

The congatec operating system (CGOS) library integrates relevant gateway system parameters, such as system temperatures, CPU workload and intrusion detection. The rule engine enables the gateway to locally initiate warnings and automated actions if certain values exceed or threaten to exceed a defined threshold. 

Finally the communication engine takes care of encrypted and provider independent data cloud communication via wired or wireless internet connections. The IoT cloud evaluation software provides the required tools for consolidating the sensor data in the cloud. Additionally, they can establish central messaging and control rules for the connected IoT applications, define further escalation scenarios and provide dashboards for remote clients.

congatec provides OEMs with all required software modules in the C++ source code, which simplifies the development of own IoT applications for Linux and Windows based on this application ready reference design and also provides additional software services for the Cloud API and its cloud connection.

Related stories: 

Edge analytics vital for security says Greenwave

By Nick Flaherty

Implementing analytics in devices at the edge of the network is the only way to prevent security breaches and potential safety threats in the workplace as the Internet of Things (IoT) continues to gather momentum in the home and industrial sector.

Current systems only deploy analytics in the gateway, and Chad Boulanger, Global VP, Business Development (IoT Analytics) at Greenwave Systems warns that as IoT deployments increase, data will not be provided quickly enough by this method to make it effective for mission critical applications. To be truly useful, according to Boulanger, analytics really need to be placed at the true edge, in devices, which has been an increasing trend followed by the Embedded blog over the last couple of years. 
“The situation we have at the moment is that data is being sent to a massive data lake where it is not being used,” said Boulanger. “As the IoT continues to grow, this is not going to add value. The only way to do that is to do as much as possible at the true edge of networks – within the actual devices – so that the machine knows that something is wrong right there and can take appropriate action. If the data has to travel from another part of the network, that could have a detrimental impact.”

This approach can be applied to IoT technology within any sector, from industrial IoT to the smart home, with its use in the latter protecting customers from security breaches, but it it down to the embedded designers to implement.

“This technology can be implemented in the home to alert users at the device level that their equipment is under attack from malware or another threat, allowing the equipment to be shut down at the earliest possible moment, potentially preventing a larger scale attack,” said Boulanger. “In industrial IoT, it is the same idea – with the implementation of edge analytics, machines can identify anomalies and shut down immediately, preventing accidents and reducing the cost of operation.”

"In a nutshell, the longer data has to travel, the longer an anomaly which could have a detrimental impact goes unnoticed. With edge analytics, such as those implemented in our AXON Predict module, machines and smart sensors can collect information at every step of the network, automatically detect anomalies and take immediate action right at the source of input.”

Greenwave Systems is a global Internet of Things (IoT) software and services company helping companies deploy their own managed services and products. Mobile carriers, telecommunications operators, semiconductor manufacturers, utilities and a wide range of service providers use the Greenwave AXON Platform to integrate data and communications from a variety of existing and emerging digital protocols. 

Related stories: 

Tuesday, March 21, 2017

Xilinx pushes machine learning and AI to the edge for embedded applications

By Nick Flaherty

FPGA designer Xilinx has launched a suite of industry-standard resources for developing advanced embedded-vision systems based on machine learning and machine inference.

Tee reVISION stack and it allows design teams without deep hardware expertise to use a software-defined development flow to combine efficient machine-learning and computer-vision algorithms with Xilinx All Programmable devices to create highly responsive systems.
The Xilinx reVISION stack includes a broad range of development resources for platform, algorithm, and application development including support for the most popular neural networks: AlexNet, GoogLeNet, SqueezeNet, SSD, and FCN. Additionally, the stack provides library elements such as pre-defined and optimized implementations for CNN network layers, which are required to build custom neural networks (DNNs and CNNs). The machine-learning elements are complemented by a broad set of acceleration-ready OpenCV functions for computer-vision processing.

For application-level development, Xilinx supports industry-standard frameworks including Caffe for machine learning and OpenVX for computer vision. The reVISION stack also includes development platforms from Xilinx and third parties, which support various sensor types.

The reVISION development flow starts with a familiar, Eclipse-based development environment; the C, C++, and/or OpenCL programming languages; and associated compilers all incorporated into the Xilinx SDSoC development environment. This will also use the Khronos Group’s OpenVX framework.

For machine learning, designers can use popular frameworks including Caffe to train neural networks. Within one Xilinx Zynq SoC or Zynq UltraScale+ MPSoC, a Caffe-generated .prototxt files can be used to configure a software scheduler running on one of the device’s ARM processors to drive CNN inference accelerators—pre-optimized for and instantiated in programmable logic. For computer vision and other algorithms, the code can be profiled to identify bottlenecks and then specific functions designated for hardware acceleration. The Xilinx system-optimizing compiler then creates an accelerated implementation of the code, automatically including the required processor/accelerator interfaces (data movers) and software drivers.

Initially, embedded-vision developers used the existing Xilinx Verilog and VHDL tools to develop systems, but the reVISION stack enables an even broader set of software and systems engineers to develop intelligent, highly responsive embedded-vision systems faster and more easily using FPGAs in new ways.

The last two years have generated more machine-learning technology than all of the advancements over the previous 45 years and that pace isn't slowing down says Xilinx. Many new types of neural networks for vision-guided systems have emerged along with new techniques that make deployment of these neural networks much more efficient. 

Related stories:

ARM takes aim at embedded AI

ARM is taking aim at embedded artificial intelligence with a new architecture.

Changes to the ARMv8 instruction set in coming processor cores will boost the performance of AI and machine learning by up to 50 times using a more flexible cluster of processor cores

The DynamIQ cluster technology will allow up to eight completely different cores to be used in a big.LITTLE style. The move is aimed at a wide range of applications, including driverless cars and automotive driver assistance systems as well as enterprise servers. This is driven by the need to have more AI processing locally, as demonstrated by the recent Jetson TX2 launch by NVIDIA. I would expect NVIDIA to be one of the major partners working with ARM on this for its own family of custom ARM-based cores.
“By 2020 we expect to see a lot of artificial intelligence deployed from autonomous driving platforms to mixed reality,” said Nandan Nayampally, General Manager of ARM’s Compute Products Group. “Even with 5G you cannot purely rely on the cloud for machine learning or AI so as performance continues to grow it needs to fit into ever smaller power envelopes.”

Extending cluster technology into embedded designs is at the heart of the ARM strategy for future devices, he says. “We started cluster with the ARM11 4-core cluster ten years ago, and then big.LITTLE was six years ago, and we used the CoreLink SoC [fabric] to scale these into larger systems,” said Nayampally.

“DynamIQ is the next stage, complementary to the existing technology, with up to 8 cores in a single clutser to bring a larger level of performance. Every core in this cluster can be a different implementation and a different core and that brings substantially higher levels of performance and flexibility. Along with this we have an optimised memory sub system with faster access and power saving features,” he said.

This would allow several small cores and several large cores to operate independently and switch code between the different cores depending on the processing requirements. “For example, 1+3 or 1+7 DynamIQ big.LITTLE configurations with substantially more granular and optimal control are now possible. This boosts innovation in SoCs designed with right-sized compute with heterogeneous processing that deliver meaningful AI performance at the device itself,” he said.

Announcements on partners and cores for DynamIQ are expected later this year with early silicon in 2018.

By Nick Flaherty

The rest of the story is at ARM to boost processor performance by 50x with new AI instructions | Electronics EETimes:

Monday, March 20, 2017

Power news this week

£10m IoT platform in Isles of Scilly for renewable energy
.£10m IoT platform in Isles of Scilly for renewable energy
Spanish buy sees Mahle enter power electronics business
.Spanish buy sees Mahle enter power electronics business
IEEE adds standard for power over Ethernet in cars
.IEEE adds standard for power over Ethernet in cars


IP aims to reduce battery fires
.IP aims to reduce battery fires

Chip-sized flow batteries could power and cool 3D stacks
.Chip-sized flow batteries could power and cool 3D stacks
Graphene supercapacitor module boosts heavy vehicles
.Graphene supercapacitor module boosts heavy vehicles

First port of capacitance power converter to 0.18μm process
.First port of capacitance power converter to 0.18μm process


Low cost SIP8 regulated DC-DC converters for 5V designs
.Low cost SIP8 regulated DC-DC converters for 5V designs
GaN FETs cut size in half with performance boost
.GaN FETs cut size in half with performance boost
Sheet transformer shrinks surface-mount isolated PoE DC-DC converters
.Sheet transformer shrinks surface-mount isolated PoE DC-DC converters


CUI: How to Stay Ahead of Efficiency Regulations for Power Adapters
.CUI: How to Stay Ahead of Efficiency Regulations for Power Adapters
Exar: Solving the Power-Up Challenge for SmartFusion2 SoC FPGAs
.Exar: Solving the Power-Up Challenge for SmartFusion2 SoC FPGAs

ZTE pushes LPWAN for large scale IoT deployments

By Nick Flaherty

ZTE is pushing low power wide area network technologies for the Internet of the Things. It has teamed up with the China LoRa Application Alliance (CLAA) to launch a shared, co-built carrier-class IoT network.

It has also launched the second generation of its Smart Street LPWAN network technology for smart city applications.
The CLAA deal provides an industrial grade IoT gateway and cloud-based core network, long range/low power (LoRa) chips/modules, intelligent IoT terminals and mature solutions together with 3D dynamic joint service provision. This is aimed at providing access over the last kilometre with low power consumption, low costs and long-distance deep coverage.

Since its foundation at the end of January 2016, the ZTE-initiated CLAA has developed into an alliance with over 500 members, displaying exceptionally fast growth. Its members include not only network enterprises which manufacture chips, devices, platforms, antennas and batteries, but also a large number of application vendors around the world with considerable experience in the metering, industry park, municipal administration, industry, energy and agriculture fields, which can boost the LoRa industry through many applications. 

The CLAA has built a technology exchange platform, solution verification platform, market cooperation platform, resource interconnection platform and innovation incubation platform for Chinese LoRa applications. It has certified over 80 products from enterprises in the alliance, released more than 50 application types and launched 30 demonstrative bases for CLAA IoT applications.

In addition to its deployments in the industrial chain ecosphere, ZTE is testing a new business and cooperation model in the LPWAN area, the CLAA network operates in an open, close-looped, shared and co-built way, and all CLAA members are builders, operators, users and application developers of the network. The CLAA has a unified and standard LoRa gateway, which enables standard hardware from different types of vendors to access a network and be shared.

ZTE has carried out trial operations in many cities, and has now entered the phase of large-scale commercial use of IoT. More than 30 smart meter enterprises have joined the alliance and support the CLAA agreement, and over 80 percent of mainstream gas meter enterprises are formal members of the CLAA. For digital oil fields, ZTE and a number of enterprises in the alliance jointly launched a LoRa technology–based production monitoring system, which can implement remote intelligent data collection and control. Compared with traditional models, this system has slashed the comprehensive construction cost and has been demonstrated in a large oil field deployment.

Smart Street 2.0 combines IoT, cloud computing platform and Big Data technologies for key services such as parking and lighting. 

“ZTE’s Smart Street 2.0 is an innovative solution for unified, intelligent and efficient street management and administration in the era of Smart City” said Yang Jun, VP of ZTE. “It modernises the street fabric and transforms the obsolete mechanism of street administration by using LPWAN technologies to improve quality of public services. The solution integrates streets’ physical infrastructure to cut costs, improve management efficiency of municipal & city governments and provides citizens with convenience and colourful experiences.”

The heart of the Smart Street 2.0 solution is the centralised ‘street command & control centre, which acts as the main back-end hub for the street applications. It interacts with smart street IoT infrastructure and collects data from the sub-systems. It then uses a Big Data analytics engine to interact with citizens via a smart phone app to provide notifications, guidance, navigation and smart routing information. It also collects payment fees for smart parking as well as other fee collections, such as traffic violation ticket charges through online payment services.

Functions like smart parking shows the real-time acquisition of available parking spaces in the street and in the vicinity of drivers, providing navigation and online payment fee facility. Smart street lights operate intelligently based on factors such as the time of the day, natural light conditions and weather. The automatic sensor technology script in the street command and control centre helps to automatically switch lights on and off or brighten/dim as per the real-time environmental conditions, natural requirements and street activity. 

Smart street LED displays can show weather, temperature, noise and other important information and can also be used for displaying public information and advertisements. The sensors also sense the volume of waste and report to the back-end system. When 80 percent capacity is reached, an automatic ‘waste pickup signal’ is sent to the back-end system, which in turn notifies the trash truck driver. It also navigates the waste collection vehicle driver to the pickup points using the most efficient route, creating a dynamic schedule for multiple waste collections in the area.

Related stories: 

Complete security certification for IoT device makers

By Nick Flaherty

Managing security keys and certificates is a considerable challenge in the Internet of Things (IoT), especially for device makers. Developing a secure public key infrastructure (PKI) is expensive and not a core part of the IoT activity, and yet it is essential.

Icon Labs is addressing this with the Floodgate Certificate Authority (CA) to provide a private PKI infrastructure for device makers using a real time operating system (RTOS).
Floodgate CA is the server side portion of Icon Labs’ PKI solution and provides certificate management for companies choosing to implement their own certificate-based authentication using public key infrastructure.

IoT security requires strong authentication. All IoT devices, including the smallest endpoints, must support mutual authentication, ensuring all communication is between known, trusted devices, and that all access is authorized. Certificate-based authentication using Public Key Infrastructure provides a proven, reliable authentication method. This is provided with connection technologies such as cellular modems, but not for other types of connectivity.

The Floodgate CA can be deployed on a hardened server or hierarchy of servers in a private environment to provide a closed PKI system without dependence upon public certificate authorities or other third-parties. It can also operate as a sub-CA of a public CA, allowing OEMs to choose the operating model based on their IoT authentication requirements.

Floodgate CA can be used with any PKI client, including Icon Labs’ Floodgate PKI Client Toolkit; an embeddable PKI client for IoT devices. Floodgate PKI Client enables even the smallest of IoT devices to generate keys, create certificate signing requests, and retrieve signed certificates from the Certificate Authority.

“This is the only security solution that provides both the client and server side required to automate secure provisioning and enrollment,” said Alan Grau, President of Icon Labs. “The Floodgate Certificate Authority and Floodgate PKI Client toolkit enables developers to easily and efficiently integrate certificate-based machine-to-machine authentication for IoT devices.”

The PKI client supports SCEP, EST, and OCSP on all RTOS, embedded Linux, and Windows devices. The Floodgate Certificate Authority encompasses a wide-range of potential use cases including key management, generating public key infrastructure certificates, and injecting pre-generated keys during the manufacturing process.

Related stories: 

Friday, March 17, 2017

Laird moves up the IoT value chain with LoRa gateway

By Nick Flaherty

Wireless module maker Laird is moving up the value chain in the Internet of Things with a long range, low power gateway using the LoRa protocol.

"The Sentrius RG1xx has been purpose-built from the ground up to create a secure, scalable, robust LoRa network solution," said Scott Lordo, senior vice president of Laird. "The RG1xx, paired with the other elements of Laird's growing Sentrius LPWAN ecosystem, enables cost-effective and end-to-end control of public and private LoRa networks alike."

The move brings together all the elements that Laird already provides for OEMs and developers  to accelerate IoT development for many of the most challenging industrial settings and applications, ranging from smart metering to equipment monitoring to municipal asset management and more.

In industrial automation, for example, full-scale networks can be used to track assets that are spread across a vast facility. A LoRa network can easily span an entire campus and gather sensor data that can provide deep insights needed to maintain efficiency, productivity and be used to make the best business decisions possible. The Sentrius RG1xx gateway helps to make a proprietary network easy to build, scale, and maintain.

The gateway uses Laird's enterprise grade 802.11 a/b/g/n MIMO Wi-Fi, wired Ethernet, Bluetooth and BLE connectivity within a single LoRa gateway, linking short-range, low-power wireless technologies with Low-Power Wide Area Network (LPWAN) technology to dramatically expand the geographic range of IoT implementations.

LoRa provides secure, bi-directional data transfer and communications with IoT networks over long distances of up to 10 miles for years without a battery change.

Based on the Semtech SX1301 / SX1257 chipset designs enabling eight channels and 27 dBm transmit power, the gateway is designed to work with Laird's LoRa ecosystem of Sentrius RM1xx LoRa + BLE certified modules and LPWAN antennas and provides compatibility with third party Cloud and LoRa partners and other LoRaWAN client devices.

The Sentrius RG1xx gateway also comes equipped with intuitive web-based configuration, integrated LoRa packet forwarder software, and default settings for multiple LoRa network server vendors. It is fully certified for FCC, IC, CE, along with a Bluetooth SIG listing.

"With multiple wired and wireless interface options, the RG1xx gives you complete design freedom to create a private end-to-end LPWAN network, which eliminates the need for a network carrier subscription," said Lordo. "The RG1xx gateway, paired with the RM1xx series of LoRa and BLE modules and Laird's LPWAN antennas, will give developers and OEMs control of their cost-effective LoRa ecosystem."

Given Laird has all the elements available already, having samples of the Sentrius RG1xx for select customers in May seems a little late. Full production follows after that, presumably if there is enough interest.

Other Related articles

Wednesday, March 15, 2017

Researchers hack accelerometers with sound waves

By Nick Flaherty

Researchers at the University of Michigan have hacked MEMS accelerometers in smartphones and IoT designs using sound waves.

By tuning into the resonant frequencies of the micro-machined sensors, the researchers, led by Kevin Fu, associate professor of computer science and engineering, could deceive 15 different models of accelerometers into registering movement that never occurred. 

"The fundamental physics of the hardware allowed us to trick sensors into delivering a false reality to the microprocessor," said Fu. "Our findings upend widely held assumptions about the security of the underlying hardware. If you look through the lens of computer science, you won't see this security problem. If you look through the lens of materials science, you won't see this security problem. Only when looking through both lenses at the same time can one see these vulnerabilities."

The researchers performed several proof-of-concept demonstrations: They used a $5 speaker to inject thousands of fictitious steps into a Fitbit. They played a malicious music file from a smartphone's own speaker to control the phone's accelerometer trusted by an Android app to pilot a toy remote control car. They used a different malicious music file to cause a Samsung Galaxy S5's accelerometer to spell out the word "WALNUT" in a graph of its readings.

"Analogue is the new digital when it comes to cybersecurity," said Fu. "Thousands of everyday devices already contain tiny MEMS accelerometers. Tomorrow's devices will aggressively rely on sensors to make automated decisions with kinetic consequences."

Autonomous systems like package delivery drones and self-driving cars, for example, base their decisions on what their sensors tell them, said Timothy Trippel, a doctoral student in computer science and engineering and first author of the paper: WALNUT: Waging Doubt on the Integrity of MEMS Accelerometers with Acoustic Injection Attacks.

Trippel noticed additional vulnerabilities in these systems as the analog signal was digitally processed. Digital "low pass filters" that screen out the highest frequencies, as well as amplifiers, haven't been designed with security in mind, he said. In some cases, they inadvertently cleaned up the sound signal in a way that made it easier for the team to control the system.

The researchers recommend ways to adjust hardware design to eliminate the problems. They also developed two low-cost software defenses that could minimize the vulnerabilities, and they've alerted manufacturers to these issues.

The university is pursuing patent protection for the intellectual property and is seeking commercialization partners to help bring the technology to market.

Related stories: 

First edge analytics integration for VxWorks

By Nick Flaherty

The Embedded blog keeps a close eye on the use of edge computing (otherwise known as good old embedded design), particularly for the potential for integrating analytics at the edge. So the move by Greenwave Systems, not a common name in embedded designs, to be the first to link up with Wind River for the VxWorks real time operating system is an interesting move. 

The boom in the number of sensors and the amount of data being produced means more analysis will have to be done at the edge, through microcontrollers with real time operating systems, FPGAs or even AI engines.

As part of this move, Greenwave has ported it AXON Predict engine to VxWorks to allow customised analytics that adds computational power and real-time intelligence throughout Industrial IoT (IIoT) embedded designs. It extends analytics and machine learning capabilities down to the chip level — and at all points in between.
“We sought to give VxWorks developers a tool with the prowess to analyze and autonomously respond to high-volume streaming sensor data at the source; our partnership with Greenwave will enable us to do just that,” said Michel Genard, general manager of operating system platforms, Wind River. “AXON Predict will provide developers with embedded analytics that learn patterns, provide insights and take actions inside connected device operations and behaviors. We’re very pleased to be working with Greenwave to offer a compelling solution to advance IIoT.”

This visual edge analytics engine, AXON Predict, will allow VxWorks developers to build a set-and-forget application with intelligence and process critical data at the edge of a network in real-time. This enables machines and smart sensors to collect information at every step of the network, automatically detect anomalies and take immediate action right at the source of input. Enhanced security features bolster the analytics engine and will provide enterprises with yet another layer of data and device protection.

“We’re excited to deliver Wind River security and predictive maintenance solutions that its VxWorks developer community can embed on their devices,” said Simon Arkell, general manager of software platforms and analytics at Greenwave Systems. “Our technology will enable them to build secure, smart things that reduce asset maintenance costs and add new functionality across myriad industries. As the first analytics solution to integrate with VxWorks, AXON Predict will automate operational efficiency in a way that was previously unattainable by those building connected devices and systems within the RTOS.” 

Related stories:

Scalable platform for 7GHz IoT radar sensor

By Nick Flaherty

Novelda in Sweden has launched a Developer Platform for sensing applications based on its second-generation ultra-wideband (UWB) impulse radar system-on-chip (SoC). 

This allows OEMs and system developers can easily implement sophisticated sensors in the INternet of Things that can detect small movements, determine presence and room occupancy, and monitor respiration and other human vital signs with unprecedented accuracy and discrimination.
Supporting various host environments, such as MATLAB, Python, C++ and C, the XeThru platform provides everything developers need to rapidly start prototyping their radar application designs. The hardware bundles an X4 SoC with an MCU board and a PCB antenna, while communications software provides an API layer that enables access to the full functionality of the SoC, and open source reference code allows the use of digital signal processing libraries to extend system performance.

Integrated into a single chip, the X4 UWB impulse radar SoC combines a transmitter, which can operate at center frequencies of either 7.29 GHz or 8.748 GHz for unlicensed operation in worldwide markets, with a direct RF sampling receiver and a fully programmable system controller. 

The X4 SoC delivers some key performance improvements over the previous design: its frame size is now configurable for different applications and the range, for simultaneous observation, has been increased from 1m to 10m, making it 10x faster and much more suitable for presence detection; its on-chip advanced power management functions enable low-power duty cycle control and dramatically reducing power dissipation; and its higher level of integration reduces external component BOM costs by more than 50%.

“The real benefit of the XeThru X4 Platform is in kick-starting the development of more advanced radar sensing applications, allowing customers who aren’t radar experts to do more than simply build a system with off-the-shelf sensors”, said Cornelia Mender, CEO, adding, “That said, we will also be upgrading our own presence detection and respiration sensors to take advantage of the enhanced performance of the X4 chip. And for customers who start with our X4M03 hardware and want to go straight to production, we will be offering the X4M02 as a single-board module that is 100% code compatible but at a lower cost in higher volumes”.

Intended specifically to aid the development of sensors based on UWB radar technology, the components of the XeThru Developer Platform include:
  • X4M03 Radar System - three interconnecting circuit boards that provide all the hardware required to prototype a target application - the X4SIP02 radarsubsystem (the X4 chip mounted on a small daughter board), the X4A02 antenna board, and the XTMCU02 MCU board.
  • XeThru Module Connector – a software suite allowing easy access to all X4M03 resources and streaming data through an API. XeThru Module Connector is distributed as a DLL / Shared Object and runs on WIN / Linux / MAC operating systems. The API is supported by Matlab, Python and C++/C.
  • XeThru Embedded Platform - open source reference code, supplied as an Atmel Studio 7 project, that will run on the X4M03 and allow developers to implement their own radar module firmware, taking advantage of an API layer that provides access to the full parameter control of the X4 SoC and the ability to process data using standard DSP libraries.
The X4 Impulse Radar SoC is the smallest UWB radar chip currently available in the market and offers unprecedented ease-of-use and BOM cost advantages. As a UWB radar solution it has been highly optimized for occupancy and respiration sensing applications and provides sub-mm accuracy with a simultaneous observation range up to 10m. Operating at below 10GHz allows it to see through obstacles and its ultra-high spatial resolution allows the detection of multiple objects. Specified for industrial temperature range applications from -40C to +85C, the chip includes advanced power management features to ensure low power consumption (typically < 120 mW).

Related stories:

Tuesday, March 14, 2017

UK spinout aims to connect the Internet of Things

An interesting story from Bristol with Sixis Technology  being launched to roll out a rugged IoT gateway.

Chris Begent with the Sixis Mini on top of a demo unit 
Sixis is a subsidiary of Telemisis which supplies end-to-end monitoring systems for power and telecoms networks. The gateway hardware and connection manager server-side software has been spun off into the new venture for other markets such as water monitoring and smart cities.

 “We aim to help system integrators and developers of Industrial IoT applications to bring their products to market more quickly and at a lower cost, by providing them with a complete Industrial IoT device solution,” said Chris Begent, Co-founder of Sixis.

“We’ve poured over 100 man-years of experience into the design and manufacture of every Sixis device solution, laying a solid foundation for any Industrial IoT application”, said the other co-founder, Tony Richardson. “The technology is already deployed with customers in over 100 countries across six continents.” One Telemisis customer has over 9000 of the gateways deployed around the world.

The Sixis Connection Manage handles communications between all Sixis devices and is deployed as part of an application on a customer server. This handles the secure communications with the gateway and provides remote device management and configuration, remote control of equipment, and ensures accurate sensor data collection and integrity. An open API allows system developers to easily include the application in a network."

See the story at UK spinout aims to connect the Internet of Things | Electronics EETimes

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Barco Silex and Imagination collaborate on IoT chip security

By Nick Flaherty

In an interesting move that highlights the fractured nature of security, Imagination is working with Belgian display company Barco Silex to add custom security to the MIPS family of processors.

Rather than using its own security technology, Imagination will integrate Barco Silex’ eSecure embedded security into a new Trusted Element (TE) IP product. The licensable TE will enhance security for customers’ connected devices.

eSecure turns ASIC and SoC designs into fully-secured hardware platforms. Under the agreement, Barco Silex will provide an embedded security solution based on eSecure which will embed a MIPS microAptiv CPU as an ultra-low power controller. Imagination will then provide customers with a range of robust security options designed around eSecure for their MIPS-based SoCs for systems as diverse as data center equipment to low-power IoT wireless sensor nodes. 

This will give Imagination’s TE secure boot, root of trust, authentication for systems that operate in a trusted execution environment, and more. In a system that uses Imagination’s OmniShield-ready MIPS CPUs for multi-domain security, this combination will provide high levels of system security performance and capabilities for connected devices.

“In an increasingly connected world, having security embedded in hardware is a must,” says Jim Nicholas, EVP, MIPS business unit at Imagination. “Imagination has been at the forefront of driving multi-domain hardware security with our OmniShield technology. Now with Barco Silex’ eSecure, we have selected a state-of-the-art solution to add a new level of hardware security to our 32/64-bit MIPS processor based subsystems. Today, our MIPS CPUs already power billions of products. By integrating this exceptional security platform, we are further strengthening that position.”

Barco Silex’ eSecure module functions as hardware root-of-trust, guaranteeing the authenticity and integrity of the application’s hardware, software, data, and communication. It offloads all security operations to hardware and scales according to the needs of the application. eSecure takes care of the secure storage and management of keys, and its cryptographic engine supports the latest algorithms for TLS/DTLS 1.3, Thread Networking, Apple HomeKit, Bluetooth, ZigBee and more.

“We are very pleased be part of this ambitious collaboration. It squarely fits with our ambition to help create secure and intuitive IoT devices, networking platforms from device to cloud and enterprise systems,” comments Thierry Watteyne, CEO of Barco Silex. “This agreement recognizes the quality of our security solutions and the reach of our expertise. In addition it will help our developers to further push our embedded security platforms beyond the state-of-the-art, especially in terms of optimizing the low-power/high-security ratio in chip architectures.”

Imagination’s range of Trusted Element IP will be available for licensing in mid-2017. 

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