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Antenova to show two new high performing 4G/LTE diversity antennas for small PCBs

By Zenobia Hegde

Antenova Ltd, manufacturer of antennas and RF antenna modules, is showing a brand new pair of high performing 4G/LTE antennas which are suitable for PCBs as small as 60mm, at the consumer electronics show CES. The two antennas can also be used in 3G and MIMO applications.

The two antennas are similar – the difference being that Inversa is built for the USA market while Integra is for European and Asian markets.

Both antennas are available in left and right versions to provide more options for placement on the PCB, and can be used singly or in pairs for MIMO. Both use beam steering to ensure good isolation and cross correlation, and achieve high performance.

Inversa, part numbers SR4L034-L /SR4L034-R, measures 28.0 x 8.0 x 3.3mm and covers the USA bands 698-798 MHz, 824-960 MHz, 1710-2170 MHz, 2300-2400 MHz and 2500-2690MHz.

Integra, part numbers SR4L049-L/SR4L049-R measures 23.0 x 8.0 x 3.3mm and covers the bands 791-960 MHz, 1710-2170 MHz, 2300-2400 MHz and 2500-2600 MHz, used in Europe and Asia.

Antenova has designed these antennas for use in small trackers, OBDs and other similar devices where space is limited. For more details, antenna samples and evaluation boards, please click here.

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Fueled by Kafka, Stream Processing Poised for Growth

By Alex Woodie

Once a niche technique used only by the largest organizations, stream processing is emerging as legitimate technique for dealing with massive amounts of data generated every day. While it’s not needed for every data challenges, organizations are increasingly finding ways to incorporate stream processing into their plans — particularly with the rise of Kafka.

Stream processing is just that – processing data as soon as it arrives, as opposed to processing it after it lands. The amount of processing that is applied to the data as it flows can vary greatly. On the one hand, users may do very little besides a simple transformation, such as converting temperatures from Celsius into Fahrenheit or combining it with another stream, while at the upper end, stream processors may apply real-time analytics or machine learning algorithms.

Almost any type of data can be used in stream processing. Sources can include a database event from RDBMs or NoSQL, sensor data from the IoT, comments made on social media, or a credit card swipe. The data’s destination similarly can be diverse – it could be headed to a traditional file system, a relational or NoSQL database, a Hadoop data lake, or a cloud-based object store.

What happens in between that initial data creation event and when the data written to some type of permanent repository is collectively referred to as stream processing. Initially, proprietary products developed by the likes of TIBCO, Software AG, IBM, and others were developed to handle streaming data. But more recently, distributed, open source frameworks have emerged to deal with the massive surge in data generation.

Apache Kafka — a distributed publish and subscribe message queue that’s open source and relatively easy-to-use –by far is the most popular of these open source frameworks, and Kafka is seen today by industry insiders as helping to fuel the ongoing surge in demand for tools to work with stream data processing.

Steve Wilkes, the CTO and founder of Striim, says Kafka’s popularity is helping to push stream processing into the center stage. “Kafka is driving a lot of our market,” he says. “A good majority of our customers are utilizing Kafka in one way, shape, or form.”

The underlying trend driving investment in stream processing is that customers need access to the latest data, Wilkes says. “It’s the recognition that, no matter how you’re doing analytics — whether you’re doing them in streaming fashion or whether you’re doing them after the fact through some sort of Hadoop jobs or big data analytics you need that up-to-date data,” he tells Datanami.

Striim this week unveiled a new release of its stream data processing solution, Striim version 3.8, that features better support for Kafka. This includes the capability to automatically scale Striim to more efficiently read from and write to Kafka as users scale up their real-time streaming architecture.

Many Kafka users are using the core Kafka product, along with the open source Kafka Connect software, to rapidly move data from its source to another destination, such as Hadoop or a data lake hosted on the cloud. Fewer shops are using the Kafka Streams API to write application logic on top of the message bus, a niche that third-party vendors are moving to fill.

According to a recent report from Confluent, the company behind open source Kafka and developer of the Confluent Platform, 81% of Kafka customers are using it to build data pipelines. Other common use case include real-time monitoring, ETL, microservices, and building Internet of Things (IoT) products.

Keeping the data lake updated with fresh data is an increasingly difficult task – and one that stream processing is being asked to fill as a sort of modern ETL role. According to Syncsort‘s recent 2018 Big Data Trends survey, 75% of respondents say that keeping their data lake updated with changing data sources is either “somewhat” or “very difficult.”

Another vendor that’s seeing the Kafka impact is Streamsets, a software vendor that bills itself as the “air traffic control” for data in motion. Streamsets’ initial product was a data collector that automated some of the nitty gritty work involved in capturing and moving data, often atop the Kafka message queue. The vendor recently debuted a low-footprint data collector that works in CPU- and network-constrained environments, and cloud-based console for managing the entire flow of customer’s data.

Streamsets Vice President of Marketing Rick Bilodeau says Kafka is driving a lot of the company’s business. “We do a lot of work with customers for Kafka, for real-time event streaming,” he tells Datanami. “We see fairly broad Kafka adoption as a message queue, where people are using [Streamsets software] primarily to broker data in and out of the Kafka bus.”

Some of Streamsets customers have a million data pipelines running at the same time, which can lead to serious management challenges. “Companies will say, ‘We built a bunch of pipelines with Kafka, but now have a scalability problem. We can’t keep throwing people at it. It’s just taking us too long to put these things together,’” Bilodeau says. “So they use data collector to accelerate that process.”

Today, Streamsets sees lots of customers implementing real-time stream processing for Customer 360, cybersecurity, fraud detection, and industrial IoT use cases. Stream processing is still relatively new, but it’s beginning to grow in maturity rapidly, Bilodeau says.

“It’s not the first inning, for sure. It’s maybe the third inning,” he says. “On the Gartner Hype Cycle, it’s approaching early maturity. Every company seems to have something they want to do to with streaming data.”

Striim’s Wilkes agrees. Fewer than half of enterprises are working with streaming data pipelines, he estimates, but it’s growing solidly. “Streaming data wasn’t even really being talked about a few years ago,” he says. “But it’s really starting to get up to speed. There is a steady progression.”

We’re still mostly in the pipeline-building phase, where identifying data sources and creating data integrations dominates real-time discussions, Wilkes says. That period will give way to more advanced use cases and people become comfortable with the technology.

“We’re seeing that a lot of customers are still at the point of obtaining streaming sources. They understand the need to get a real-time data infrastructure,” he says. “The integration piece always comes first. The next stage after you have access to the streaming data is starting to think about the analytics.”

Related Items:

Spark Streaming: What Is It and Who’s Using It?

How Kafka Redefined Data Processing for the Streaming Age

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Spirent adds BeiDou Phase-3 signals to its GNSS RF constellation simulators

By Zenobia Hegde

Spirent Communications plc, the provider in BeiDou, GPS and other global navigation satellite systems (GNSS) testing solutions, announced that BeiDou Phase 3 signals have been added to its GNSS RF constellation simulators.The addition of these new signals to the GSS7000 and GSS9000 simulators follows the launch of the first two Beidou-3 satellites in November 2017.

Phase 3 of the Chinese BeiDou system will extend its coverage from Asia to the whole world, and will provide receiver developers and integrators with additional GNSS signals to make positioning, navigation and timing systems more accurate, and help to support new applications, such as autonomous vehicles.

The new signals will use the same carrier frequencies as the GPS and Galileo systems, so chipset manufacturers and device developers will need to test integrated designs to avoid problems caused by confusing data from different GNSS.

“By offering the BeiDou Phase 3 signals, our customers can test their designs well before the system is fully operational, which is expected in 2020,” said Stuart Smith, lead product manager. “With signals already starting to appear, it is important for developers to have test tools that can ensure devices will successfully make use of all GNSS signals.”

BeiDou Phase 3 signals are available immediately on the GSS7000 and GSS9000 simulators, and existing users can obtain the software upgrade by contacting Spirent.

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Machfu Announces Release of MACH-3 Industrial Internet of Things Platform and Gateway

By IoT – Internet of Things

Machfu, an Industrial Internet of Things (IIoT) technology company, announced today the release of its MACH-3 IIoT Gateway, a device allowing companies in energy, water, oil and gas as well as other industrial segments to seamlessly connect legacy infrastructure to cloud based IoT and existing SCADA systems. The product was designed to both simplify the […]

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Machfu announces release of MACH-3 IIoT platform and gateway

By Zenobia Hegde

Machfu, an Industrial Internet of Things (IIoT) technology company, announced the release of its MACH-3 IIoT Gateway, a device allowing companies in energy, water, oil and gas as well as other industrial segments to seamlessly connect legacy infrastructure to cloud based IoT and existing SCADA systems.

The product was designed to both simplify the connection and management of devices as well as provide a secure and easily customisable application framework to process and manage data at the network edge. The versatile functionalities of the MACH-3 IIoT Gateway will be demonstrated at the 2018 DistribuTECH show, January 22-25 in San Antonio, Texas.

“The MACH-3 IIoT Gateway allows companies to securely gather actionable data from legacy infrastructure in an elegant and straightforward manner, enabling them to make informed, strategic business decisions in ways that would previously require enormous financial and time investments,” said Prakash Chakravarthi, CEO, Machfu.

Deployment of this platform enables enterprises to easily access and analyse data from diverse sources (i.e. sensors, controllers, smart grids, etc.) via secure wireless and wired connectivity as well as create and rapidly integrate “edge” and “emerging web-based” industrial IoT applications to existing infrastructure.

The application framework is “sandboxed” providing enterprises much needed flexibility in terms of adding/deleting APPs and drivers over the life of their system—much like a smartphone—based on their specific needs and/or requirements. Defense-in-depth security has also been built into the platform and extends from the physical to application layers.

“The resulting IIoT solutions decrease time to action and connectivity costs, while, simultaneously, minimising disruption and risk to existing automation systems,” added Chakravarthi.

There are many practical applications and benefits for the MACH-3 IIoT Gateway in the energy industry. “Using Machfu’s industrial hardened gateway, utilities can create and rapidly integrate next generation distributed control systems,” said John Geiger, V.P. business development, Machfu.

“For example, the Gateway provides the ability for any sensor to be transported as DNP3 objects to head-end SCADA applications over both private and public networks. It also provides a secure cellular overlay to existing private networks. The flexibility and versatility of the platform is its greatest asset.”

Machfu will be demonstrating the product at DistribuTECH 2018 held January 22-25 in San Antonio, TX (Booth 1862).

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