The Embedded Blog: 2019

Friday, December 27, 2019

Monday, December 23, 2019

Wireless charging tags and pacemakers ... GaN transistors for space and avionics

Power news this week at eeNews Europe by Nick Flaherty www.flaherty.co.uk

. Meyer Burger sells Dutch industrial inkjet business

. Estonia launches smart city project with Finland

. Smart luggage tags are charged remotely

. Power modules double EV inverter performance

POWER TECH TO WATCH

. Fast charging lithium aqueous battery

. Spherical graphite boost for silicon anode battery technology

. Tiny battery-free pacemaker is wirelessly charged

. 650V rugged GaN transistor for military and space designs

. Selecting GaN transistors for avionics power

. Programmable DC power supply adds ModBUS-TCP interface

TECHNICAL PAPERS

. Industrial robot ransomware

. We’re All Part of the Automotive Evolution

. Building secure processor-based systems with faster time-to-market

Thursday, December 12, 2019

Smart hub combines wired and wireless protocols

By Nick Flaherty www.flaherty.co.uk

Bridgetek has launched a smart hub that combines wired and wireless protocols for building automation.

The technology is used in the recent PanL Smart Living and PanL Room Manager systems. The PanL Hub enables installers to incorporate various different communication technologies into their system deployments, so that greater functionality can be derived while still ensuring maximum user convenience and keeping down costs.

In terms of wireless connectivity options, Wi-Fi (802.11b/g/n), ZigBee and RF433 protocols are all included, plus more specialist OEM-specific protocols like Hue, DALI and DMX512. Consequently, the PanL Hub is able to interact with the broadest possible variety of wireless smart devices (both sensors and actuators) within environments like homes, offices, hotels, retail outlets, etc. There are no limitations imposed by the communication technology of the device, thereby allowing control of everything (heating, lighting, air conditioning, room/building access and so on) directly through intuitive PanL-based user interfaces.

The wireline connectivity allows the PanL Hub to hook up to the building’s existing Ethernet (10/100 Base-T) infrastructure through standard CAT 5/6 cabling, with PoE capabilities meaning that power can be drawn via this route, as well as using it for data transfer.

There are 2 different configurations available - with the PanL Hub 44 featuring 4 serial ports for display unit connection and the PanL Hub 80 expanding that to a total of 8 serial ports for this purpose. The PanL Hub 44 can connect directly to 8 PanL70/PanL70Plus display units through these serial ports (with another 4 serial ports dedicated to interfacing with sensors), while the PanL Hub 80 can connect to 16 of these. There is scope for multiple hubs to be hooked up to the network and cascaded - so that any size of office facility or residential complex can potentially be addressed.

The foundation of the PanL Hub is a 64bit quad-core ARM Cortex A53 microcontroller with 1GB of low-power DDR2 RAM memory resource and 4GB of embedded flash available. It runs the Linux operating system to simplify the integration into different building automation scenarios and to adapt it if needed.
www.brtchip.com

Tuesday, December 10, 2019

50GOPS at 50mW for IoT AI edge processor

By Nick Flaherty www.flaherty.co.uk

GreenWaves Technologies has launched a new member of its GAP IoT application processor that cuts the energy consumption by a factor of 5.

The GAP9 combines architectural enhancements and Global Foundries 22nm FDX process to deliver a peak cluster memory bandwidth of 41.6 GB/sec and up to 50 GOPS combined compute power at an overall power consumption of 50mW.

GAP9 enables customers to embed machine learning and signal processing capabilities into battery operated or energy harvesting devices such as IoT sensors in smart building, consumer and industrial markets and consumer and medical wearable devices. Compared to the GAP8, GAP9 reduces energy consumption by 5 times while enabling inference on neural networks 10 times larger.

“GAP9 enables a new level of capabilities for embedding combinations of sophisticated machine learning and signal processing capabilities into consumer, medical and industrial product applications,” said Loic Lietar, CEO of GreenWaves Technologies. “The GAP family provides product designers with a powerful, flexible solution for bringing the next generation of intelligent devices to market.”

GAP9 adds support for floating-point arithmetic with an FPU that handles 8, 16, and 32-bit precision with support for vectorization. GAP9 also extends GAP8’s support for fixed-point arithmetic with support for vectorized 4-bit and 2-bit operations. This helps make the calculatons more power efficient.

The GAP9 also incorporates bi-directional multichannel, synchronized digital audio interfaces for wearable audio products, as well as CSI2 and parallel camera interfaces allowing the use of low resolution, low power camera for scene analysis and then extract a region of interest from high-resolution, higher power camera for analysis of scene details.

GAP9 handles sophisticated neural networks such as MobileNet V1, processing a 160 x 160 image with a channel scaling of 0.25 in just 12ms with a power consumption of 806μW/frame/second. GreenWave has boosted the effective memory bandwidth compared to GAP8 by a factor of 20, enabling significant improvements in detection accuracy by simultaneously analysing streams of data from multiple different sensors such as images, sounds, and radar.

GAP9 incorporates additional security features protecting device makers firmware and models while also protecting devices from tampering including hardware support for AES128/256 cryptography and a Physically Unclonable Function (PUF) unit that allows devices to be uniquely and securely identified.

The GAP SDK includes the GAP AutoTiler, allowing automatic code generation for neural network graphs often reducing memory movement down to below 1.2 times the theoretical minimum and GAPFlow, a series of tools for automating the conversion of neural networks from training packages such as Google TensorFlow. Combined with out of the box, open-source, network implementations such as a full, Open Source Face Identification implementation, the GAPFlow toolset reduces implementation time from months to days.

www.greenwaves-technologies.com.

Monday, December 09, 2019

Smallest 100nF capacitors for 5G phones ... startup creates network of power packs ... Nexeon silicon anode patents

Power news this week by Nick Flaherty www.flaherty.co.uk

. Murata launches world's smallest 100nF MLCC ceramic capacitor for 5G smartphones

. Nexeon acquires 24 key battery patents

. UK startup creates network of charging power packs

. Battery management deal for Croatian electric hypercar

. Project to develop aluminium nitride AlN power transistors and system designs

. 120W eighth brick encapsulated DC-DC converter for railway and industrial

. 24V three phase digital industrial power supply delivers over 4kW

Wednesday, December 04, 2019

CodeGuru gives automated code reviews and application performance recommendations

By Nick Flaherty www.flaherty.co.uk

Amazon has launched a cloud-based machine learning service for development teams who want to automate code reviews, identify the most expensive lines of code in their applications, and receive intelligent recommendations on how to fix or improve their code.

Even for the most seasoned engineers, it can be difficult to detect some types of code issues even through peer code reviews and unit testing. It can also be challenging to identify the most resource intensive code methods without needing performance engineering expertise. CodeGuru, based on the AWS cloud service, helps developers catch code issues faster and earlier, and improve application performance.

CodeGuru Reviewer detects and flags wide-ranging issues in source code such as thread safety issues, use of un-sanitized inputs, inappropriate handling of sensitive data, and resource leaks. It also detects deviation from best practices for using AWS APIs and SDKs, flagging common issues that can lead to production issues, such as detection of missing pagination or error handling with batch operations.

It is based on machine learning models trained on Amazon’s internal code bases of hundreds of thousands of internal projects, as well as over 10,000 open source projects in GitHub. Tens of thousands of Amazon developers have contributed to CodeGuru’s training based on decades of experience in code review and application profiling.

For example, CodeGuru Reviewer is trained using rule mining and supervised machine learning models that use a combination of logistic regression and neural networks. During training to detect deviation from best practices, it mines Amazon code bases for pull requests that include AWS API calls. It looks at code changes and cross-references them against documentation data, which it also mines in parallel. This creates new models for best practices that Reviewer uses when it reviews the code to provide recommendations. CodeGuru Profiler is also trained by Amazon performance engineers and used to profile tens of thousands of services used internally at Amazon.

The Profiler searches for application performance optimizations, identifying the most “expensive” lines of code and recommending ways to fix them to reduce CPU utilization, cut compute costs, and improve application performance. This provides specific recommendations so developers can take action immediately on issues such as excessive recreation of expensive objects, expensive deserialization, usage of inefficient libraries, and excessive logging. It also runs continuously in production, consuming minimal CPU capacity so it does not significantly impact application performance.

To use the service, developers can associate existing code repositories on GitHub or AWS CodeCommit with CodeGuru. Profiling an application starts by installing a small agent using code that CodeGuru provides and configuring it in the CodeGuru console.

CodeGuru is available in preview in the AWS regions of US East (N. Virginia), US East (Ohio), US West (Oregon), EU (Ireland), and Asia Pacific (Sydney).

Amazon CodeGuru

Kontron Box PC industrial controllers use Intel Core and Xeon E processors

By Nick Flaherty www.flaherty.co.uk

Kontron has launched its third generation of industrial computers in Box PC format using Intel Core and Xeon E processors

The KBox C-103-CFL series is based on the latest of the ninth generation with up to six processor cores and are specifically designed for use in control cabinets in automation environments. In addition to the control and visualization of machines or inspection and AI-based vision applications, Soft-PLC applications can also be implemented using the optional NVRAM and the integration of fieldbus extensions. The KBox C-103-CFL is currently available with two PCI Express slots; further variants with up to four slots will follow during the first quarter of 2020.

The Bix PCs use the ninth generation Core i3, i7 or Xeon E processors; the Intel Core i5 is based on the 8th generation. The maintenance-free system enables fanless operation up to 75 degrees Celsius while a Goldcap option and redundant power supplies as well as the recovery functionality guarantee maximum system availability and a long life time.

In addition to up to three display ports and up to four GB Ethernet interfaces, the family features up to four PCI Express, one mPCIe and three M.2 expansion slots. Up to two COM ports incl. RS485 option, three USB 3.0 and three USB 2.0 ports,as well as up to four SATA slots ensure maximum flexibility and expandability. For secure communication and connection to the cloud, the industrial computers support TPM V2.0 encryption and the Kontron APPROTECT security solution based on Wibu-Systems CodeMeter. Kontron APPROTECT Licensing also enables new business models such as 'pay-per-use' or time-based trial versions.

www.kontron.com/products/systems/embedded-box-pc/kbox-c-series/kbox-c-103-cfl.html

Tuesday, December 03, 2019

AMD gets back into the embedded market with focus on mini PCs

By Nick Flaherty www.flaherty.co.uk

AMD has made its return to the embedded market with Ryzen Embedded V1000 and R1000 processors.

These are being used by ASRock Industrial, EEPD, OnLogic and Simply NUC for Mini PC platforms for the industrial, media, communications and enterprise markets with a planned 10-year processor availability.

“The demand for high performance computing isn’t limited to servers or desktop PCs. Embedded customers want access to small form factor PCs that can support open software standards, demanding workloads at the edge, and even display 4K content, all with embedded processors that have a planned availability of 10 years,” said Rajneesh Gaur, corporate vice president and general manager of Embedded Solutions, AMD. “This is why many of our technology partners have chosen AMD Ryzen Embedded processors to power their Mini PCs. We are excited to work together and provide the industry with a new open ecosystem for small form factor computing.”

The value this time, says AMD, is the Mini PCs have access to an existing embedded processor ecosystem that supports open software standards, while providing OEMs the capability to create unique, customisable platforms.

The AMD Ryzen Embedded processors combine the Zen CPU and Vega GPU architectures in an SoC with a power envelope from 6W to 54W in pin compatible packages that powers high resolution, 4K multi-display configurability and high-performance 3D graphics.

The key is that the Mini PCs support a growing list of software partners with pre-validated packages based on open source software. These partners include Radeon Open Compute (ROCm), OpenCL™, and more. As well, these Mini PCs can run software for machine vision, object detection, edge inference, and analytics from AMD software ecosystem partners, creating a platform that’s well suited for applications that require fast deployment.

ASRock Industrial with its 4X4 BOX – R1000V and 4X4 BOX – V1000M systems aim to deliver cost-effective, high-performance and versatile embedded Mini PCs for home entertainment, business and industrial applications.
EEPD's SBC PROFIVE NUCV and SBC PROFIVE NUCR embedded Mini PC product family is focussed on minimal space
OnLogic's ML100G-40 and MC510-40 are the first two systems in a line of AMD powered small form-factor computers that leverage the reliability and lifecycle benefits of OnLogic's expertise in building industrial and rugged devices.
Simply NUC with the Sequoia V8 and Sequoia V6, which are rugged, long-lasting units to power digital signage displays, electronic kiosks, data arrays, and other free-standing utilities

"Simply NUC has excelled in making small form factor PCs for a while, but when we took a look at our product roadmap, we noticed a gap in providing our customers with high-performance, long life platforms," said Aaron Rowsell, CEO at Simply NUC. "With the new Simply NUC Sequoia platform, we get to take the high-performance capabilities and planned longevity of the AMD Ryzen Embedded processors and combine that with the Simply NUC experience and create a minicomputer that’s small in size but not on toughness or reliability.”

AMD Ryzen Embedded Processors

Monday, December 02, 2019

Adlink teams for machine vision AI at the edge

By Nick Flaherty www.flaherty.co.uk

Camera maker ADLINK Technology has teamed up with Intel and Amazon Web Services (AWS) to simplify artificial intelligence (AI) at the edge for machine vision.

The integrated solution offers an Amazon Sagemaker-built machine learning model optimized by and deployed with the Intel Distribution of OpenVINO toolkit, the ADLINK Edge software suite, and certification on AWS Greengrass.

The approach provides the full cycle of machine learning model building—from design to deployment to improvement—by automating edge computing processes so that customers can focus on developing applications without needing advanced knowledge of data science and machine learning models:

The Intel Distribution of OpenVINO toolkit optimizes deep learning workloads across Intel architecture, including accelerators, and streamline deployments from the edge to the cloud.
Amazon Sagemaker is a fully-managed service that covers the entire machine learning workflow.
AWS Greengrass extends AWS to edge devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage.
The ADLINK Data River offers translation between devices and applications to enable a vendor-neutral ecosystem to work seamlessly together.

“We’ve worked on multiple industrial use cases that benefit from AI at the edge, including a smart pallet solution that makes packages and pallets themselves intelligent so they can detect where they're supposed to be, when they're supposed to be there, in real-time,” said Toby McClean, VP, IoT Innovation & Technology, at ADLINK. “This enables warehouse customers to yield improved logistics and productivity, while also decreasing incorrectly shipped packages and theft. And this use case can be replicated across verticals to improve operational efficiency and productivity.”

Additional use cases include object detection modeling for object picking functions or worker safety, such as identifying product defects on conveyor systems or worker impediments in manufacturing environments, and equipment failure predictions to reduce machine downtime and increase productivity.

The software can be fully optimized on certified ADLINK devices, including the NEON industrial smart camera, EOS vision system, and deep learning accelerator card and GigE frame grabber with Intel's Movidius Myriad X VPU.

Hybrid wafers with GaN on Si ... Spin computing slashes power ... In-panel batteries to boost storage

Power news from eeNews Europe Power by Nick Flaherty www.flaherty.co.uk

. Spin computing slashes power consumption

. Nexans signs wind turbine power cable deal with Siemens Gamesa

. Swedish 50kW fast charger roll out uses ABB tech

. Silicon-carbon anode startup raises $18m

POWER TECH TO WATCH

. Graphene battery electrode for in-panel storage

. Hybrid GaN-on-SiC wafers boost for power devices

NEW POWER PRODUCTS

. 300Farad UL-certified ultracapacitor for robotics and smart factories

. 1U programmable power supply reaches 3.4kW

. 600A, 60mm bipolar thyristor module targets drives and UPS

TECHNICAL PAPERS

. Ground Bond or Ground Continuity?

Friday, November 29, 2019

Kontron expands COMe Type 6 boards with AMD Ryzen processors

By Nick Flaherty www.flaherty.co.uk

Kontron is expanding its portfolio of COMe-cVR6 (E2) Computer-on-Modules in the COM Express Compact Type 6 form factor with new variants of AMD's Ryzen processor.

These will use the Ryzen V1404I with 4x 2.0 GHz and a power consumption of 12 to 25W. Versions with ECC memory down or with DDR4 SO-DIMM socket are possible. Both are designed for the industrial extended temperature range between -40 and +85 degrees Celsius. This makes the COMe-cVR6 modules particularly suitable for use in harsh environmental conditions, such as power utilities or in the defence sector, as well as for applications in medical imaging or industrial image processing, and for complex automation systems.

The COMe-cVR6 (E2) computer-on-modules are based on the AMD Embedded V1000 processors, and the smaller form factor of the COM Express Compact Modules allows significantly more space to be saved. This enables developers to produce more compact designs with maximum performance. In addition, the COMe-cVR6 (E2) variants with soldered-on memory are insensitive to vibration and shock. All other components such as voltage dividers, capacitors and controllers have also been chosen in regards to ensuring maximum resistance to environmental influences.

The new COMe-cVR6 (E2) supports the Kontron APPROTECT security solution based on Wibu-Systems CodeMeter. In addition, Kontron APPROTECT licensing also enables new business models such as 'pay-per-use' or time-based trial versions.

The modules are expected to be available during the first quarter of 2020.

www.kontron.com/products/boards-and-standard-form-factors/com-express/com-express-compact/come-cvr6-e2-.html

Friday, November 22, 2019

Global regulators identify mmWave spectrum for 5G services

By Nick Flaherty www.flaherty.co.uk

After a month of 'difficult' negotiations, regulators at the ITU’s World Radio Conference (WRC-19) meeting this week agreed a range of frequency bands for millimetre wave 5G service.

This impacts on the antenna and chipset designs going forwards for mobile handsets, hubs and wireless links for the Internet of Things (IoT) as well as determining the data bandwidth that will be available for services.

Over 10 GHz of spectrum for 5G in the 26, 40, 47 and 66 GHz ranges was agreed.

"GSA members have participated in the difficult negotiations that have taken place in the run up to this decision, particularly with regards to 26 GHz, keeping in mind the need to protect satellite services in the adjacent spectrum while remaining committed to delivery of high–performance economical solutions to the global markets," said the Global mobile Suppliers Association (GSA).

"The GSA is also delighted that administrations have agreed to study additional spectrum opportunities in the mid-band frequencies between 3.3 and 10.5 GHz, as well as spectrum below 1 GHz. This will help enable 5G services to be further deployed in wider geographical areas, including rural areas, as well as meet the anticipated increased traffic needs of population centres in the next decade."

“The Industry forecast is that by 2024 over 130 Exabytes of data will be transmitted globally every month and the mobile industry will need to massively deploy 5G technology in a broad range of frequency bands to meet this demand," said Joe Barrett, President of the GSA. "Applications that will drive this massive data usage include 8k mobile video, Augmented and Virtual Reality, HD video, industrial automation and robotics, drone and aeronautical networks and the IoT.

"Spectrum regulators have recognized that low-, mid- and high-band frequencies need to be available and harmonised globally as much as is possible to ensure mobile broadband can meet the expanding services both industry and consumers are expecting in the coming years," he said.

There are 183 5G devices from 72 vendors tracked in the GSA GAMBoD database, with at least 42 are commercially available: https://gsacom.com/paper/5g-device-ecosystem-november-2019/

There are now 50 5G commercial networks in 27 countries. By the end of October 2019, 328 operators in 109 countries had announced they were investing in 5G: https://gsacom.com/paper/50-5g-commercial-networks-november-snapshot/

5G Modems Chipsets + LTE & IoT: Status Update: https://gsacom.com/paper/5g-modems-chipsets-status-update-2/

Thursday, November 21, 2019

Advantech launches palm-sized PC with Atom 3900 for IoT

By Nick Flaherty www.flaherty.co.uk

Advantech has launched a palm-sized embedded controller measuring 170 x 117 x 52.6mm based on the latest Intel Atom E3900 processor technology to give a 30% CPU performance enhancement and a 45% graphic performance boost. It is also certified for use with the AWS Greengrass and Microsoft Azure IoT Edge cloud services for the Internet of Things.

The EPC-U2117 is designed with dual display output, multiple I/O, and 12 to 24V DC power inputs, which target smart vending machines, digital signage, smart kiosk, and more.

It runs Microsoft Windows 10 IoT Enterprise and Linux OS as well as Advantech’s WISE-PaaS DeviceOn intelligent software integrated for remote system monitoring and management that also BIOS/FW OTA updates to upgrade the system and devices with latest firmware to keep everything running at peak performance.

THe unit can be mouted as a desktop PC, or via wall, or DIN-Rail mount. The top extruded aluminium passive heatsink thermal solution is designed for -20 ~60 °C wide temperature operation and there are integrates two expansion slots including one M.2 for Wi-Fi or GPU module, and one full size Mini PCIe for 3G/LTE connection or mSATA storage.

The EPC-U2117 supports multiple storage, which includes onboard eMMC up to 128GB, mSATA, and 2.5” SSD/HDD for flexible storage options. Customers can install OS and key data in eMMC for best security protection and reliability. If customer request big storage capacity and high data transfer, they can use mSATA or SATA SSD for better storage performance.

Monday, November 18, 2019

Infineon teams with Klika Tech on smart buildings

By Nick Flaherty www.flaherty.co.uk

Infineon Technologies has teamed up with Klika Tech to connect smart buildings to the cloud. The partnership brings together Infineon’s chips with Klika Tech's Cloud technology based on Amazon Web Services (AWS).

“Klika Tech is a strong addition to Infineon’s partner network, offering complementary capabilities to develop innovative solutions for smart building applications,” said Oliver Henning, Head of Partnership Management & Emerging Application Business at Infineon’s Power Management & Multimarket division. “

Klika Tech is a global developer of end-to-end networks in the Internet of Things (IoT) using cloud-based services. It is using Infineon's chips for product development, as well as rapid development kits with full AWS cloud integrations. The companies are focusing on end-to-end solutions across applications such as smart building, smart city, smart home, connected devices as well as autonomous and electric cars.

“Collaborations among hardware, software and services providers are the genesis of the custom IoT and Cloud solutions that are enabling companies to reduce their development efforts and expedite time to market. This holds especially true for smart building and smart home applications.” said Gennadiy M. Borisov, President and Co-CEO at Klika Tech. “We look forward to building on our relationship with Infineon and the integration of their outstanding sensor portfolio with AWS services.”

Cloud-based Machine Learning (ML) algorithms provide predictive maintenance capabilities for current equipment condition analysis, informs maintenance personnel, and can trigger specific tasks to keep machines running at optimum levels. Implementing a predictive maintenance plan can detect improper installation, make equipment more energy efficient, predict costly failures, and extend equipment life to reduce total costs of ownership.

www.klika-tech.com