Smart Cities Archives - Page 455 of 570 - SmartCitiesElectronics.com

Skyline RFID inlays and tags can be used on metal

Thu, Aug 08, 2019

Rain radio frequency identification (RFID) inlays can be used on metal surfaces for and have a reading range of 6m.

The Skyline Rain RFID inlays and tags have an optimised antenna and spacer-based design. A customised ultra high frequency (UHF) inlay is based on NXP’s UCODE 7xm IC with 448-bit EPC memory and extended user memory of 2kbits. The resulting transponder is then folded and applied around a synthetic spacer developed and provided by identytag of Bad Berleburg, Germany.

The advanced antenna design, the IC’s long read range and reliable operation in dense reader and noisy environments through high interference rejection, as well as optimised spacer material result in an on-metal read range in a compact tag, with a die-cut size of 54 x 25 x 1.8mm.

The inlay is permanently attached to the spacer and a layer of strong and resilient RA-33 adhesive is applied. According to Smartrac, this provides “excellent adhesion” to a range of surfaces. As a finished tag, Skyline’s surface is printable with thermal transfer printers.

The RFID tag can be used for tracking metallic assets, items and components in industrial environments such as automotive, mechanical engineering and aviation. Smartrac’s Skyline inlays and tags comply with VDA recommendations for the automotive industry and supported by the leading automation companies globally.

Smartrac and identytag completed initial product volumes and will be ramping up production in the second half of the year 2019.

Smartrac provides both ready-made and customised products. It makes products smart and enables businesses to digitise, identify, authenticate, track and complement products. Products are used in a wide array of applications such as animal identification, automation, automotive, brand protection, customer experience, industry, library and media management, logistics, retail and supply chain management.

Based in Amsterdam, the Netherlands, Smartac has research and development centres, production and a sales network, complemented by the IoT platform, Smart Cosmos. Smartrac embeds intelligence into physical products for an ecosystem of connected things. The company has also received ARC Quality Certification from Auburn University’s RFID Lab for the design and manufacturing of its RFID inlays.

http://www.smartrac-group.com

> Read More

Xilinx introduces PCIe Gen 4 card for critical data centre workloads

Wed, Aug 07, 2019

Believed to be the industry’s first adaptable compute, network and storage accelerator card which delivers “dramatic improvements” in throughput, latency and power efficiency for critical data centre workloads, says Xilinx.

The Alveo U50 has been added to the Alveo data centre accelerator card range. It is claimed to be the industry’s first low profile adaptable accelerator with PCIe Gen 4 support. According to the company, it boosts a range of critical compute, network and storage workloads in a single, reconfigurable platform.

The Alveo U50 is a programmable low profile and low-power accelerator built for scale-out architectures and domain-specific acceleration of any server deployment, on-premise, in the cloud and at the edge, says Xilinx. It is intended to meet the challenges of emerging dynamic workloads such as cloud microservices and delivers between 10 to 20 times improvements in throughput, latency and power efficiency. The principle is to move the compute closer to the data to help developers identify and eliminate latency and prevent data bottlenecks and thus accelerate networking and storage.

The U50 is powered by the Xilinx UltraScale+ architecture. It is the first in the Alveo family to be packaged in a half-height, half-length form factor and low 75W power envelope. The card features high-bandwidth memory (HBM2), 100Gbit per second networking connectivity, and support for the PCIe Gen 4 and CCIX interconnects.

The 8Gbyte of HBM2 delivers over 400Gbits per second data transfer speeds and the QSFP ports provide up to 100Gbits per second network connectivity. The high-speed networking I/O also supports advanced applications such as NVM Express over Fabrics (NVMe-oF), disaggregated computational storage and specialised financial services applications.

Applications for the Alveo U50 are machine learning inference, video transcoding and data analytics to computational storage, electronic trading and financial risk modelling. For deep learning inference acceleration (speech translation), the Alveo U50 delivers up to 25 times lower latency, 10 times higher throughput and better power efficiency per node compared to GPU-only for speech translation.

For data analytics acceleration (database query), the Alveo U50 runs the TPC-H Query benchmark to deliver four times higher throughput per hour and reduced operational costs by a factor of three, compared to in-memory CPU. It also delviers 20 times more compression/decompression throughput for computational storage acceleration (compression). It also has faster Hadoop and big data analytics, and over 30 per cent lower cost per node compared to CPU-only nodes.

In electronic trading applications, the U50 delivers 20 times lower latency and sub-500 nanosecond trading time compared to CPU-only latency of 10 microseconds. In financial modelling applications, the Alevo U50 runs the Monte Carlo simulation and delivers seven times greater power efficiency compared to GPU-only performance, reports Xilinx.

Xilinx will be showcasing the Alveo U50 at the Flash Memory Summit 2019 (6 to 8 August) at the Santa Clara Convention Center in Santa Clara, California, USA.

The Alveo U50 is sampling now with OEM system qualifications in process. General availability is scheduled for Q3 2019.

http://www.xilinx.com

> Read More

Microchip reduces power needs for AI functions

Wed, Aug 07, 2019

Compute power for artificial intelligence (AI) inference at the edge is reduced, says Microchip, when using the memBrain neuromorphic memory technology.

AI processing is moving from the cloud to the edge of the network, meaning that battery powered and deeply embedded devices are challenged to perform AI functions, such as computer vision and voice recognition.

Via its subsidiary, Silicon Storage Technology (SST), Microchip offers the memBrain which is based on SuperFlash technology and optimised to perform vector matrix multiplication (VMM) for neural networks. The memory technology is claimed to improve system architecture implementation of VMM through an analogue in-memory compute approach, which, in turn, is claimed to enhance AI inference at the edge.

Current neural net models may require 50M or more synapses (weights) for processing which can challenge off-chip DRAM bandwidths, causing a bottleneck for neural net computing and an increase in overall compute power. The memBrain stores synaptic weights in the on-chip floating gate, which significantly improves system latency, says Microchip. Compared to traditional digital DSP and SRAM/DRAM based approaches, it delivers 10 to 20 times lower power and “significantly reduced overall bill of materials (BOM)”.

The memBrain is expected to advance machine learning (ML) capacities in edge devices, with reduced power in memory compute operations in AI.

SST will present Microchip’s memBrain product tile array-based architecture at the AI/ML session track on flash performance scaling at the 2019 Flash Memory Summit this week (6 to 8 August 2019) at the Santa Clara Convention Center in Santa Clara, California, USA.

SST offers design services for memBrain and SuperFlash technology and a software toolkit for neural network model analysis.

Silicon Storage Technology provides embedded flash technology in addition to developing, designing, licensing and markets proprietary and patented SuperFlash memory technology for the consumer, industrial, automotive and IoT markets.

SST was founded in 1989 and acquired by Microchip in April 2010 and is now a wholly owned subsidiary of Microchip.

http://www.microchip.com

> Read More

Automation engine manages IoT across countries and networks

Fri, Aug 02, 2019

Arm has announced Pelion Connectivity Management 2.0, an automation engine to scale the IoT and automatically manage millions of devices across multiple countries and different networks.

The company believes that a single platform for managing IoT connectivity across all a mobile network operator’s (MNOs) devices’ lifecycles. Arm says MNOs can drive additional revenue opportunities by enabling their enterprise clients the capability to automatically configure IoT devices. The automation capabilities are claimed to significantly improve the IoT services, speed and reliability of connectivity, which can be the provisioning of new devices or ensuring monthly bills never go over a set threshold.

Automation capabilities include real-time data triggers to create rules that are triggered by what is happening in the physical world.

The seamless remote subscriber identity module (eSIM) provisioning management ensures the correct service and commercial configuration and IoT deployment operational costs can be reduced, adds Arm.

The company believes Pelion Connectivity Management 2.0 will help enterprises overcome the challenges of moving from pilot IoT projects to a global scale, which enterprises have not been able to achieve before as manually managing every device across multiple countries and different mobile networks had not been possible until now.

“With our enterprise customers increasingly expanding internationally, as well as the rise of new technologies such as NB-IoT and eSIM, we wanted an IoT connectivity management service that can provide a single pane of glass regardless of underlying technology, MNO or geography,” said Carlos Lourenço, director corporate IoT business unit, of Portugal’s mobile network operator, NOS.

Michele Mackenzie, principal analyst, Analysys Mason, believes this introduction will accelerate IoT adoption. “Network operators and enterprise customers might start with small estates of devices but look to scale up quickly as the benefits of IoT are realised,” she said. “For millions (and potentially billions) of devices to be connected to telecoms networks in a timely, cost efficient, scalable way platform services will need to become increasingly automated.”

http://www.arm.com

> Read More

Skyline RFID inlays and tags can be used on metal

Xilinx introduces PCIe Gen 4 card for critical data centre workloads

Microchip reduces power needs for AI functions

Automation engine manages IoT across countries and networks

About Smart Cities