IoT Design Guide 2018

SUMMER 2018 | VOLUME 5 WWW.EMBEDDED-COMPUTING.COM

IOT INSIDER

PG 6 Processing 5G Workloads

2018 Design Guide Industrial IoT Forecast: MISTY

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IoT Research Reveals Evolution of the Embedded Engineer

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5 Avnet – Does your IoT Strategy have a Connection Problem?

13 Avnet – Don’t be lulled into a false sense of IoT security 1 Digikey – IoT Development TO Kit Selector electronica 2018 – COME Meet the world, shape the future

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Sealevel Systems, Inc. – Push the Edge

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Virtium LLC – Balance is Everything

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IoT Design Guide 2018

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www.embedded-computing.com/iot

Connecting Global Competence

Summer 2018 | Volume 5

CONTENTS

opsy.st/IoTDesign

FEATURES

10 VDC Research identifies IoT trends, evolution

10

of the “embedded engineer”

By Curt Schwaderer, Editorial Director

14 Getting misty eyed over Industrial IoT

By Brian MacLeod, CRATUS Technology, Inc.

18 Bluetooth 5 and Bluetooth mesh: Enabling use cases for

By Pelle Svensson, u-blox

22 Beyond the Bluetooth beacon: Why today’s application

22

By Paddy McWilliams, CEVA http://bit.ly/OpenSourceRISCV5

 Populating smart devices with the right IQ

By Fabio Belloni, Quuppa

By Amit Gattani, Micron Technology

24 Firmware security for IoT devices

http://bit.ly/TheRightIQ

 Raspberry Pi 3 B+ boosts the Pi 3’s processing and communication capabilities

By Dick Wilkins, UEFI Forum, Phoenix Technologies, Ltd., and Thomas College

By Jeremy Cook, Engineering Consultant

26 Hybrid IoT platforms deliver simplicity, flexibility, and fast time to market for the Internet of Things

By Terrence Barr, Electric Imp

 AI, IoT, and the digital healthcare revolution

NB-IoT Wireless

IOT INSIDER –

5G networks find flexibility in FPGA-based modems

By Brandon Lewis, Technology Editor

Qualcomm advancing LTE modems in preparation for 5G

By Curt Schwaderer, Editorial Director

 Domain experts take on data science

By Seth DeLand, MathWorks

By Rich Nass, Editorial Director http://bit.ly/AIHealthRevolution

COLUMNS TRACKING TRENDS –

http://bit.ly/RPiBoost

http://bit.ly/DomainExperts

30 2018 Design Guide

8

With increasing desire to move more intelligence and connectivity closer to the edge of Internet of Things networks, industry is pushing through the fog and towards mist computing.

Mist computing trends, strategies, and implementations are covered on page 14 of this issue. Some of 2018’s most innovative IoT products and solutions can also be found in the Design Guide, beginning on page 30.

 Open source RISC-V architecture is changing the game for IoT processors

requirements have moved beyond what beacons can offer

6

COVER

WEB EXTRAS

Industry 4.0

Development Kits Industrial

@iot_guide

Published by:

9

AUTOMOTIVE ANALYSIS –

Connectivity looks prominent in infotainment’s 2018 diary

By Majeed Ahmed, Automotive Contributor

2018 OpenSystems Media® © 2018 Embedded Computing Design All registered brands and trademarks within Embedded Computing Design magazine are the property of their respective owners. iPad is a trademark of Apple Inc., registered in the U.S. and other countries. App Store is a service mark of Apple Inc. ISSN: Print 1542-6408 Online: 1542-6459 enviroink.indd 1

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IoT Design Guide 2018

10/1/08 10:44:38 AM

www.embedded-computing.com/iot

SPEAKOUT

ADVERTORIAL

Does Your IoT Strategy Have a Connection Problem?

By Lou Lutostanski

The Internet of Things isn’t just a buzzword, it’s a business opportunity. According to industry analysts, there’s vast potential economic value in IoT projects going forward.

However, many organizations are struggling to get their projects off the ground.

Why? It comes down to building a solid business case for IoT and then lining up the resources to execute on it.

The Internet of Things relies on one word: Connection What is IoT without the connection that brings devices together? Businesses strug­gle to scope and deploy IoT initiatives because, compared to traditional information technology projects, they require more hardware and software integration as well as more security considerations, from end to end.

Your operational technology team has the experience of managing networks in the field and your information technology unit knows administering data and network computers backwards and forwards.

In IoT, these teams’ expertise must work together within any solution you deploy.

End-to-end security means that hardware and software in every step of the process must remain secure. This means ensuring mutual authentication as well as message integrity and confidentiality to ensure each piece of technology is communicating securely throughout the solution, too.

IoT forces that connection to extend beyond technology, too. What is IoT without the connection between different parts of the business? IoT challenges traditional business models by negotiating the needs and perspectives of a myriad of stakeholders and potential service providers. Some say it might take up to 10 partners to get an IoT project started.

Connection, whether in-house or external Your business approach to IoT needs to function much like the technology itself: keep everything connected, with information flowing quickly and smoothly between all nodes.

The key to a smooth implementation is your partnership structure. Each IoT use case is unique to your particular business, so building an in-house team can be a large investment with a large reward. However, it takes time, money and commitment to secure that talent in-house – and there’s not as much unbiased vetting of that customized solution, especially considering the evolving best practices and security issues that spring up overnight in the world of IoT. In the Internet of Things, the devil’s in the details.

Give your IoT solution a point person The likelihood that a one-size-fits-all approach will work for your implementation is slim. The complexity in IoT requires deep expertise and experience across a variety of areas. How much time will it take to chase down 10 partners when something goes wrong? Have you mapped out the right product road map that someone can refer back to throughout the lifecycle of your solution?

A huge market means there’s a lot of noise. Having more partners increases your risk of failure and cost because it decreases your ability to collaborate and communicate well, and therefore reduces your agility. Yet, it’s nearly impossible to ignore the opportunity in IoT. Make sure that there is a lead partner that will take responsibility for your IoT solution, maintenance and all.

IoT INSIDER

5G networks find flexibility in FPGA-based modems

By Brandon Lewis, Technology Editor

blewis@opensystemsmedia.com

If you buy into the hype, 5G networks are poised to revolutionize the current wireless infrastructure. Headline capabilities of 5G technology include peak 20 Gbps download and 10 Gbps upload speeds, 1 ms latencies, up to 1,000x greater capacity per km2 than 4G, 3x spectrum efficiency, 100x better network energy efficiency, and the integration of multiple radio access technologies into a single network (Figure 1).

Many, if not all, of these characteristics make 5G extremely attractive for the Internet of Things (IoT).

In fact, many 5G IoT deployments have already begun. Beyond demonstrations of 5G at the 2018 Olympics in Pyeongchang, South Korea, the University of Bristol’s Smart Internet Lab recently deployed an end-to-end 5G network testbed in Bristol City. The testbed demonstrates a variety of smart city use cases, including autonomous transportation, augmented reality, and smart tourism, which are enabled by 5G New Radio (NR) radio heads connected to a virtual 5G baseband pool.

5G NR is the new air interface for 5G networks. Although it is not backwards compatible with LTE, 5G NR does provide spectrum coverage from sub-1 GHz to 100 GHz. Signals are sent from 5G NR radio heads over a new orthogonal frequency-division multiplexing (OFDM) wireless standard, which uses closely-spaced sub-carrier signals to send data simultaneously across several parallel channels.

Many current 5G network architectures deploy these NR radio heads in base stations with massive multiple-input, multiple-output (MIMO) antennas that use multiple transmitters and receivers to transfer more data, more quickly. Such infrastructure can support various access and connectivity scenarios for applications like enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC).

More traditional distributed small cells and fixed wireless access points will also remain, but the constant requirement across all 5G infrastructure is the need for extreme

FIGURE 1 According to the International Telecommunications Union (ITU), 5G (shown here as IMT-2020) is projected to deliver significant advantages over 4G (shown as IMT-Advanced), including triple the spectrum efficiency, 100x energy efficiency, and 1,000x capacity.

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IoT Design Guide 2018

flexibility. This has led many carriers, telecom companies, and researchers such as the University of Bristol to implement software-defined networking (SDN) capabilities as the backbone of their 5G networks. Raghu Rao, Principal System Architect, Wireless Communications at Xilinx, explains this transition.

“One aspect is the variety of deployment types we are seeing in 5G,” Rao says.

“The physical layer is being split, with a portion of the physical layer moving to the radios, especially in the context of this new massive MIMO technology.

And then we have small cells and home gateways. And then we also have fixed wireless access. Then we have the traditional macro cell and metro cell sort of deployments. So if you look at the variety of deployments, what you need is extreme flexibility. A software-driven approach is a lot more capable of supporting this diversity than a 100-percent hardware scenario like it used to be in 4G, where everything was in a box.

“The other aspect to that is the support for various spectrum,” he continues. “In 5G there is sub-6 GHz and greater than sub-6 GHz. Now, even if you look at the traditional sub-6 GHz deployments, there’s a huge range of frequencies on which one wants to talk. In the case of License Assisted Access (LAA) and LTE-Unlicensed, you’re talking about anchoring an unlicensed carrier with a licensed carrier with over a GHz of gap between them. Some of these deployments require extreme flexibility, even on the RF side of things.

“Both of these place certain requirements on the design of the hardware at the infrastructure site,” Rao says. “There are different types of access and connectivity coming into the picture, all of them www.embedded-computing.com/iot

connecting to the same packet core using similar types of infrastructure and similar standards.

“What we see people looking for is a very, very flexible modem,” he adds.

5G flexibility on FPGAs As Rao points out, the underlying base station hardware must be able to accommodate the broad requirements of 5G network workloads. This is driving increased interest in FPGA technology across the next-generation wireless infrastructure.

“There are aspects of a modem that cannot entirely be software on a server or software running on a x86 processor, such as extremely compute-intensive tasks,” Rao says. “The approach that we see people taking is the software-plusacceleration approach, especially at what we call layer one, or the physical layer.

Those workloads are accelerated, and a great choice for acceleration is FPGAs.” In Q4 2017, Xilinx announced its Zynq UltraScale+ RFSoC product line that, among other use cases, targets the 5G wireless RF signal chain. RFSoCs incorporate analog-to-digital and digital-toanalog converters (ADCs/DACs) that operate at up to 4 GSps and 6.4 GSps, respectively, as well as soft-decision

forward error correction (SD-FEC), a quad-core Arm Cortex-A53, and a dual-core Arm Cortex-R5 alongside programmable logic fabric (Figure 2). The company states that the devices provide a 50 to 75 percent power and footprint reduction over competing SoC-based architectures for use in remote radio heads for massive MIMO, baseband, and wireless backhaul systems.

The integrated data converters in RFSoC chips are particularly advantageous in systems with multi-mode requirements, as they can dynamically support 3GPP LTE and NB-IoT simultaneously, for instance. Rao describes this versatility by returning to the example of licensed and unlicensed carriers sharing the same platform.

“The RFSoC architecture supports what we call ‘direct RF’ where you can sample at extremely high speeds,” he says. “Sampling at those high speeds allows the rest of it to be done digitally, possibly in the FPGA, and so it can be moved into a software-like approach. All of this supports a considerably flexible, programmable modem.

“Depending on the deployment scenario, a single RFSoC can handle multiple workloads,” Rao continues. “It could be reconfigured or the configurations could be built in ahead of time. There are certain workloads like Massive MIMO that would require multiple RFSoCs, but there are many others where one or two RFSoCs are perfectly capable.”

Beyond base stations While Xilinx expects RFSoC technology to be deployed in 5G base stations everywhere, the company is also seeing interest in small cell settings, macro cells, virtual baseband units, cloud radio access networks (RANs), and even telecom clouds. As network infrastructure is increasingly governed by software, expect FPGA technology to appear in places you wouldn’t normally suspect.

“Everyone is looking for a low cost, quickly deployable system, and for that FPGAs are a great solution. Time to market and all of those advantages help FPGAs in many of the remote radio head deployments,” Rao says. “But baseband is a is a new kind of use for our devices. We used to find a spot in baseband for connectivity reasons. But this new, flexible, software approach to baseband has opened up newer opportunities for FPGAs to maximize throughput and increase power efficiency.” IoT DSP-Based Mixing & Filtering

Decimation

I/Q or Real

IQ Mixers

Gain/Phase Compensation

4GSPS 12-bit

RF Signal

RF ADC

NCO

Logic Fabric

Interpolation I/Q Mixers

I/Q or Real

Gain/Phase Compensation

6.4GSPS 14-bit

RF DAC

NCO

Digital Up-Conversion & Down Conversion

FIGURE 2

RF-Class Performance

Flexible Multi-Band Support

Xilinx Zynq UltraScale+ RFSoCs integrate multi-GSps RF data converters and forward error correction (FEC) in support of 5G infrastructure applications that require spectral efficiency, power efficiency, and network densification.

www.embedded-computing.com/iot

IoT Design Guide 2018

7

TRACKING TRENDS

Qualcomm advancing LTE modems in preparation for 5G

By Curt Schwaderer, Editorial Director

cschwaderer@opensystemsmedia.com

Qualcomm recently announced the X24 LTE modem, which is based on 7 nm process technology and boosts throughput to 2 Gbps while lowering power consumption. These advancements help increase performance, efficiency, and user experience as networks advance towards 5G. Undoubtedly, the X24 LTE modem delivers impressive technical numbers. But what do they mean to the mobile industry and subscribers? David McQueen, Director of Handsets and Device Platforms, ABI Research has answers.

McQueen notes that Qualcomm has always been a leading supplier to the mobile phone market from a client and customer perspective. The company has been involved with LTE modems and RF for a long time, but the X24 announcement fills out an LTE product portfolio that addresses high-end applications as 5G rolls out.

“As an LTE modem play, Qualcomm has been a leader in the smartphone arena. Samsung and Huawei have been trying to create their own modems, but Qualcomm has a heavy lead in this space,” McQueen notes. “The announcement of the X24 Snapdragon LTE modem helps the smartphone user with faster response, ability to run virtual reality applications, faster upload to cloud-based storage, and almost instantaneous app usage. The X24 provides a proper broadband experience for the things emerging for LTE and coming with 5G. From an operator perspective, the X24 also provides efficient use of network spectrum for LTE and 5G.” Coinciding with the X24 release, Qualcomm announced that Telestra and Ericsson have plans to leverage the technology.

McQueen observes that the X24 announcement also seems to be a stepping stone to the X50 5G modem, which is scheduled for sampling in 2019. The X50 is expected to use the X24 as the fallback to gigabit LTE.

Snapdragon 845 Mobile Platform

Specs

Qualcomm has revealed a roadmap of 5G silicon for the next two years. Currently, though, several Qualcomm mobile platforms exist that may support X24 modems in the near future (Table 1).

X24 pricing is still unavailable, but McQueen expects the parts to show up in high-end devices first until economics make the technology mainstream.

Research shows smartphones prepping for 5G transition A research paper developed by Signals Intelligence was recently published that compares the performance of Cat 16 gigabit LTE smartphones and Cat 12 smartphones. The tests measure each type of device by running common mobile data applications over LTE-Advanced networks that don’t necessarily support gigabit LTE data rates. The goal of the study was to demonstrate the benefits of Cat 16 smartphones regardless of the mobile data application or LTE network version under a variety of radio conditions[1].

Measuring frame freezes and impairments while streaming video to determine quality and bandwidth efficiency across LTE networks supporting one to four LTE radio channels, the study concluded that Cat 16 LTE smartphones delivered a measurably “better user experience while requiring substantially fewer network resources than a Cat 12 LTE smartphone.” The study continues to contrast Cat 16 gigabit LTE and Wi-Fi. 5G is coming, and with the announcement of technologies like the X24 LTE modem with its performance, network efficiency, and power benefits, the path is getting smoother.

References: 1. Qualcomm LTE modem user experience benchmarking white paper developed by Signals Research Group. https://www. qualcomm.com/documents/gigabit-lte-and-user-experience.

Snapdragon 835 Mobile Platform

Snapdragon 821 Mobile Platform

Snapdragon 820 Mobile Platform

Current Modem

Snapdragon X20

Snapdragon X16

Snapdragon X12

Snapdragon X12

CAT

Category 18

Category 16

Category 13

Category 13

Downlink

1.2 Gbps

1 Gbps

600 Mbps

600 Mbps

Upload

150 Mbps

150 Mbps

150 Mbps

150 Mbps

Video

4K ultra HD 60 FPS

4K ultra HD 30 FPS

4K ultra HD 30 FPS

4K ultra HD 30 FPS

Speed

2.8 GHz

2.45 GHz

2.4 GHz

2.2 GHz

TABLE 1 8

Current mobile platforms from Qualcomm that could support the X24 LTE modem.

IoT Design Guide 2018

www.embedded-computing.com/iot

AUTOMOTIVE ANALYSIS

Connectivity looks prominent in infotainment’s 2018 diary

By Majeed Ahmed, Automotive Contributor

After smartphones, cars are becoming the next extension of the connected lifestyle. This is apparent given how much connectivity has taken center stage in automotive infotainment designs. Look at the major infotainment announcements during the past six months or so where connectivity is the key design theme.

The 2018 Audi A8, for instance, allows drivers and passengers to connect up to eight devices at one time to an Alpine Wi-Fi hotspot. The Wi-Fi hotspot communication unit was designed by e.solutions, a joint undertaking of Audi and Elektrobit, and based on the CYW89359 combo 802.11ac and Bluetooth connectivity solution from Cypress Semiconductor (Figure 1). Thus, it allows two unique data streams to run at full throughput simultaneously.

The CYW89359 supports 2.4 GHz and 5 GHz 802.11ac, as well as dual-mode Bluetooth/Bluetooth Low Energy (BLE) streams. The chip is based on the Real Simultaneous Dual Band (RSDB) architecture that integrates two Wi-Fi subsystems into a single chip, which enables concurrent operation of communications technologies like Wi-Fi and Apple CarPlay without any degradation from switching between RF bands.

Another design that showcases the importance of connectivity to infotainment systems is Valens’ HDBaseT Automotive technology that allows simultaneous transmission of HD video and audio, Ethernet, and control data over a single, unshielded twisted pair (UTP) cable for up to 15 meters. Figure 2 shows the Valens solution operating in the context of a distributed playback invehicle media distribution system from Cinemo, which employs the Accordo5 infotainment and Telemaco3P telematics processors from STMicro. www.embedded-computing.com/iot

FIGURE 1

The combo 802.11ac and Bluetooth connectivity solution from Cypress Semiconductor can stream high-fidelity video and audio content simultaneously.

FIGURE 2

A view of Valens’ HDBaseT Automotive in-vehicle connectivity platform.

Finally, Microchip’s smart hub IC portfolio for in-vehicle USB designs consists of five chips based on the USB 2.0 standard. The automotive-grade semiconductors cater to multiple vehicle architectures so that multiple manufacturers and Tier 1s can interface with major smartphone platforms.

The Microchip USB chips enable the cascading of hubs to the second and third rows of vehicle seating. In addition, if dual USB ports are available, the devices permit one to be used for connecting to a mobile device and the other for data transfer or wireless charging.

With so much activity around connected silicon for automotive infotainment platforms, it’s only a matter of time until we can truly classify all vehicles as endpoints on the Internet of Things.

IoT Design Guide 2018

9

SPECIAL FEATURE

VDC Research identifies IoT trends, evolution of the “embedded engineer”

By Curt Schwaderer, Editorial Director

Over the past year, I’ve written a couple of pieces about a new breed of engineer that spans embedded, network, and cloud skill sets. Earlier this year, I wrote a blog about IT services companies promoting combined embedded and IT staff, frameworks, and services. I also did some research into staffing organizations and their efforts to actively address these hybrid positions.

VDC Research recently published a couple of interesting research reports that provide critical insight into this trend and its impact going forward. Critical mass has formed and VDC has segmented out the “IoT Engineer” as its own marketplace because of its markedly different set of requirements for IoT systems and applications development.

The IoT Developer/Engineer Census and Analysis report conducts polls and interviews of the global embedded/IoT engineering population related to what kinds of challenges it faces, as well as the kinds of tools, software, hardware, and frameworks needed to address them.

The Voice of the IoT Engineer 2017: Survey Dataset and Analysis report is an analysis of responses from an annual survey of IoT and embedded engineers, managers, and decision makers. The research looks at IoT device development, technology adoption trends, vendor perception, and strategies, which are segmented by vertical market, geography, processor architecture, operating system, and programming language.

Together, these research reports are a signpost that shows how IoT is blurring the lines between enterprise IT and embedded. Roy Murdock, a VDC Research analyst and one of the authors of the reports, recently shared some important takeaways from these studies.

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IoT Design Guide 2018

Study drivers The studies segment embedded and IT, then give growth rate trends and projections. The research contains specifics, but Murdock states that more than 55 percent of the embedded population is now employed as IoT engineers.

“The majority of embedded engineers are now working on connected projects with cloud and/or IoT involvement in some way,” Murdock says.

VDC defines an IoT engineer as someone who works on a project that includes www.embedded-computing.com/iot

networking and connectivity technology to enable the exchange of data, communication, and services between devices, machines, and/or network infrastructure and the backend or cloud (Figure1).

According to Murdock, former embedded engineers are now embracing new development methodologies to keep pace with evolving requirements.

“Key tools these IoT engineers use include, more recently, IoT cloud Platformsas-a-Service (PaaS),” Murdock says.

“This is driving the need for new skills.

Amazon Web Services (AWS) IoT, GE Digital Predix, Microsoft Azure IoT Suite, PTC ThingWorx, and Siemens MindSphere are examples of IoT platforms that these engineers are using to drag, drop, connect, analyze, and develop applications for IoT systems. These environments require engineers to know their way around IT networking as-aservice, security, and API integration.

“... PYTHON IS NOW BEING USED REGULARLY TO CLEAN, TRANSPORT, AND MANIPULATE THE DATA THAT COULD RESIDE IN THE CLOUD OR ON IOT GATEWAYS.”

sparingly in embedded projects in the past for scripting and testing, but rarely implemented in the embedded projects themselves,” Murdock continues. “Our most recent embedded surveys and studies show that Python is now being used regularly to clean, transport, and manipulate the data that could reside in the cloud or on IoT gateways (Figure 2). The data science discipline is also becoming a key skill set within the embedded domain as analytics add greater differentiation to IoT systems and applications.”

Software Engineer 2017

Test/Verification/Validation Engineer

2022 Mechanical Engineer Algorithm Developer/Functional Expert System Architect/Engineer

“Strong vertical domain knowledge of the enterprise and their products and services is critical. These aren’t skills that are being taught in school – they are emerging skills that are resulting from socializing OT and embedded engineers with IT and cloud developers within these IoT projects,” he adds.

Is embedded adopting IT, or vice-versa?

Project Manager Board Engineer IC/SoC Engineer Other Engineer

FIGURE 1

While there are significant embedded and real-time implications in IoT systems, Murdock mentions that IT engineers may be better positioned to cross over into embedded IoT engineering roles.

“IT and enterprise developers usually understand data analytics and data wrangling already, albeit from different enterprise networks and data sets. This may give them an inside track to apply these same patterns and paradigms to IoT systems residing in these cloud services and IoT gateway platforms.”

IoT Developer/Engineer Census: Global Embedded Engineering Population, Segmented by Role (Millions of Engineers) Previous

51.5%

16.1%

Python

25.5%

30.7%

20.8% 23.6% 20.1%

Java

16.0%

JavaScript

14.5%

20.7% 21.1%

24.0% 20.0%

17.1% 17.4% 17.8%

C# 5.8% 5.4% 7.0%

In-house developed 0%

FIGURE 2

59.4% 58.1%

41.9% 43.0% 44.4%

C++

Still, the vertical domain knowledge that embedded engineers often bring is a necessary part of the IoT equation.

www.embedded-computing.com/iot

Expected in 3 Years

C

Assembly

“In the IoT it’s often critical to understand the embedded device and what data is being generated. One example of change in recent years has been the adoption of Python, which was used

Current

10%

20%

30%

40%

50%

60%

70%

Voice of the IoT Engineer: Languages Used to Develop Software in Previous, Current, and Future Projects (Percent of Respondents) IoT Design Guide 2018

 11

Special Feature Murdock adds that the deeply embedded, safety-critical system area where safety concerns and strict real-time requirements exist still require traditional embedded engineering skill sets. Automotive, aerospace and defense, industrial automation, medical devices, and energy are a few verticals where systems with low latency and real-time guarantees are needed. However, many systems within these verticals, such as automotive infotainment, medical wearables, and industrial gateways, are crossing into the realm of the Internet-connected.

Key takeaways In terms of the engineering workforce, the studies breakout populations by vertical market and geography. They consider who is working in certain roles, in particular regions, and in given industries.

“The studies are geared toward giving the reader a sense of the embedded and IoT population. From there, we look at different embedded roles such as project managers, algorithm engineers, mechanical engineers, etc. We then further break these out into nearly a dozen vertical categories and perform forward projections based on a mix of primary and secondary data, and the identified trends,” Murdock says.

Another interesting takeaway is tool attach rates. What tools are being used and attach rates for IDEs, prototyping solutions, and static analysis tools, with many other tool types covered, are forecasted out through 2022. Apparently, tool adoption has reached the point where performing attach rate analysis is warranted.

Murdock also provided analysis on the three-to-five-year horizon of embedded and IoT. While there will still be separate embedded and IT disciplines five years from now, there will be increasing pressure for mixed IoT skill sets, as well as significant payoffs.

“Skill sets and value are being condensed into fewer and fewer engineers,” Murdock observes. “For example, Intel acquired Mobileye for $15.3 billion.

Mobileye employed fewer than 500 people at the time of the acquisition. These high dollar M&A numbers with increasingly fewer people are a sign of things to come with more and more value locked into fewer skilled IoT employees. People able to get into the most domain-specific roles like Mobileye has in the auto industry and extend skills from embedded to IT or vice versa will drive the lion’s share of value going forward.” IoT References: 1. “IoT Developer/Engineer Census and Analysis.” Accessed March 22, 2018. http://www.vdcresearch.com/Newsevents/info/Engineer-Census.html.

2. “Voice of the IoT Engineer 2017: Survey Dataset and Analysis.”

Accessed March 22, 2018. http://www.vdcresearch.com/Coverage/ IoT-Tech/reports/17-Voice-of-the-IoTEngineer.html.

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IoT Design Guide 2018

www.embedded-computing.com/iot

SPEAKOUT

ADVERTORIAL

Don’t be lulled into a false sense of IoT security

By Guillaume Crinon

The Internet of Things (IoT) is here and expectations have never been higher – not only about new innovations in the field, but also how secure those innovations will be. That’s why nine out of every 10 consumers worry about IoT security, whether its device hacking, sensitive data leaks or unauthorized access.

It’s true, end users don’t really care which wireless protocol or encrypted chip ensures a secure system. But you still have to balance the big business opportunity around IoT with the big security challenges it presents, all on faster timelines and with more data breaches than ever.

There’s just one problem: that’s really hard to do.

In fact, a recent survey found that only 40 percent of service providers said they would be completely ready for a breach within the next two years. Yet, 40 percent of IoT specialists assume their service provider will never have a security breach.

Don’t be lulled into a false sense of ­security in IoT. Here’s what you should consider to build a secure solution: Start with a secure element: Deploy a strong security chip able to play the role of a solid root of trust and perform crypto­functions such as encryption, decryption, true random number generation, signature and verification – basically what keeps secrets safely hidden from the outside world.

Give it a unique identity: Implement identity through unique serial numbers, MAC addresses, IEEE device addresses, private and public key pairs. Have the public keys signed by a Certificate Authority (CA) and turn them into X.509 certificates establishing their validity inside a Public Key Infrastructure (PKI).

Stack these hardware and software security solutions end-to-end: Manage these secure elements through a variety of life-cycle services such as personalization, certification authority, PKI/key management, identity management and upgrade services.

Don’t forget about the other endpoints, too: Make sure it’s as hard as possible for the devices at each end of your security scheme to be compromised.

Smartphones and gateways are as critical to security as your connections in the cloud.

Help devices do the basics: Ensure each “thing” in your IoT solution can speak the same language as every other device in a deployment, securely communicating in a way that only the other devices in your solution can see so it can’t be hacked by outsiders.

You need to be prepared for breaches at any point in your IoT solution, through any provider, via an end-to-end security scheme. Follow the steps to ensure your team’s security plans are airtight, or get the right partner who can help you through that process.

Thinking about this ahead of time will save you a lot of headache on the backend. Unless you’re dying to test out that age old saying that “there’s no such thing as bad PR.”

WIRELESS CHIPSETS

Getting misty eyed over Industrial IoT

By Brian MacLeod, CRATUS Technology, Inc.

The Industrial IoT (IIoT) is beginning to move beyond concept to reality. The simple concepts of “cheap sensors everywhere,” “data to the cloud for analysis,” and “dashboards on your browser” are giving way to more nuanced and realistic models. Recent articles have explored this trend with discussions of fog or edge computing[1]. This is a good first step, but it is not the complete picture.

Mature IIoT systems will also include mist computing, which involves moving compute closer to the sensors than in what would normally be considered fog computing. In any given application, mature IIoT deployments will likely include a mix of these architectural concepts, including mist-cloud, mist-fog, and mist-fog-cloud. Driven by the increasing capabilities of microcontrollers, systems-on-chips (SoC), and low-cost communications, mist computing will be an important component of millions of solutions.

A recent TV ad shows a family scrambling to find the TV remote. In the background, one family member asks Amazon’s Alexa to select the correct channel. Alexa processes the request and sends commands to the Dish TV Hopper box. Within a short time, the family has settled down to watch, and the remote is forgotten.

The time taken to process the TV control loop is probably faster than it takes to find the mislaid remote controller (especially if the dog has carried it off to a

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different room). This is good, but do you want a nuclear power station controlled this way? How about an air traffic control system or the emergency alert system at your chemical plant?

This example highlights that the IoT splits into at least two major models: The consumer model and the industrial model. The consumer model usually involves the centralization of data followed by decision making in the cloud.

This is a perfect model for offering free or low-cost functions or services where

the bulk of data gathered can be monetized in other ways. The classic example is Google, where search or email is offered for free but the collected data is monetized in advertising services.

There are other, less-obvious examples, such as smart electric meters. The meter is on your house, but the data is gathered centrally, and you only get access via a carefully created utility website.

Most of the data is used by the utility for other purposes, primarily cost reduction, demand response, fault diagnosis, and system planning (Figure 1). www.embedded-computing.com/iot

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Industrial IoT

IIoT versus consumer IoT

cloud[2]. Fog computing may involve a single edge device or multiple edge devices operating together. There are many combinations, and most examples will work in conjunction with cloud resources (Figure 2).

Cloud Computing

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FIGURE 2

IIoT architecture showing the relationship between mist, fog, and cloud computing. The most common wireless links are identified together with handheld and web-based human-machine interfaces.

IIoT is different With IIoT applications, there are other concerns: latency in the control loop, lower reliability due to a long chain of elements involved in the decision process, cost of data transmission and storage, and security of sensitive operational data (Sidebar 1).

To alleviate these concerns, Arm, Cisco, Intel, Microsoft, and others have proposed edge computing as an alternative[1]. Here, an edge device or a set of edge devices contains business logic and can make decisions locally or regionally, without reference to, or cooperation with, a central core. The concept has become known as fog computing to note the decentralized nature and distinguish it from the centralized www.embedded-computing.com/iot

Data, intelligence, insight.

Sensor data is shared with mist computing resources.

Derived intelligence is passed to fog computing resources. Only essential intelligence and/or data are sent to the cloud.

There is, however, another factor at play.

By gathering up all sensor data, we risk overwhelming systems with a mix of relevant and irrelevant data. We receive so much data that it is hard to figure out what to do with it. This is similar to the problem of “alarm fatigue” suffered by pilots in aircraft cockpits and medical staff in hospital intensive care units[3].

The better approach is to derive intelligence from the sensor data and only transmit the intelligence to the decision-making site (fog or cloud). In ideal circumstances, the intelligence is derived close to the sensors, not in fog or cloud-computing locations. This concept is becoming known as mist computing (Figure 3).

Here, the idea is to use low-cost microcontrollers to do more than data conversion and simple communications.

The processing power is used to look at streams of data from multiple sensors and derive inferences and complex IoT Design Guide 2018

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Wireless Chipsets insights. We can also look at the condition of the sensors themselves. This approach may yield additional understanding of what is happening at the location or assist with maintenance cycles.

“CLOUD PLATFORMS ARE READILY AVAILABLE,

Sensor platforms to the rescue Fortunately, advances in sensor platforms, such as the CRATUS Technology/Fujitsu BlueBrain system[4], and powerful microcontroller families, such as the Arm Cortex series, make this an economic and straightforward approach. Platforms such as these contain a mix of sensors, I/O, computing resources, communications, and development resources, making it easier to prototype a solution for an individual problem or application. If the required volume is low, the sensor platform can be used as a final solution. If the volume is high, a custom design can be crafted to reduce a platform’s hardware and software costs (Figure 4).

At the Sensors Expo & Conference, CRATUS and Fujitsu demonstrated an example of mist computing by directly tying two BlueBrain sensor platforms to a Microsoft HoloLens headset. This demonstration of augmented reality (AR) used sensor data from the BlueBrain platform directly overlaid onto a visual that could be seen through the HoloLens, and was achieved on a Cortex-M4 processor without additional edge, handheld, or cloud computing. This is an example of how feedback and control can be provided in an industrial setting where complexity in the visual field makes it hard

SIDEBAR 1

WHY NOT CLOUD? The leading reasons are:

•• Latency is the measure of the round-trip time from the sensor to the cloud and back again. There are uncertainties in the communication system.

How far away is the data center with the cloud server? Is the cloud server heavily loaded? For time-critical situations, this is less than optimal.

•• Privacy of data is a great concern. Sensitive commercial information may be embedded in the data, and a competitor could gain advantage by accessing this data. What about a stock raider gaining insight and using it in the stock market?

•• Security can be compromised at any point. If data is sent to a remote location for analysis and storage, there are many more system entry points than in an edge setup. If the data involves critical operating information, the overall security of the operation or enterprise may be compromised.

•• Reliability is lower for cloud solutions. All things being equal, more devices mean lower reliability.

•• Critical infrastructure industries are now required to assess the vulnerability of infrastructure. Governments mandate what must be done, and there are fines and penalties.

•• Persistent connection may not always be available. What happens when the cloud is not available 100 percent of the time?

•• Storage and retrieval costs can skyrocket when unnecessary data and intelligence is sent to the cloud. Not only does this cost in terms of power and communications, but there are also costs to store and to retrieve data (communications and access fees).

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SO ONE MAY ASK, ‘WHY BOTHER?’ RECENT WORK GIVES US CLUES: THERE ARE SAVINGS IN COMMUNICATION, POWER, AND, BY IMPLICATION, STORAGE COSTS.”

to distinguish cause and effect. Direct systems of this nature support humanmachine collaboration and improve safety in dangerous environments.

Why bother?

Cloud platforms are readily available, so one may ask, “Why bother?” Recent work gives us clues: There are savings in communication, power, and, by implication, storage costs[5]. A recent IEEE article compared three different approaches from pure cloud to pure edge, and the resulting savings were significant.

Similar benefits can be gained by using computing resources close to the sensors. In this case, the communications will usually be wireless, so in addition to the benefit of bandwidth, mist computing reduces the RF noise and interference levels from the billions of IIoT devices that are expected to be deployed.

The bottom line: Mist is already here Current IoT and IIoT solutions are onedimensional – they are typically deployed to address one need or use case. The true benefits of IoT technology will appear when we have multiple systems cooperating to help with a bigger picture. This work cannot be done in the cloud for all use cases. Fog and mist devices need to be flexible. They must be open to having additional functions overlaid long after initial deployment. www.embedded-computing.com/iot

The increasing power of microcontrollers and recent advances in software-defined sensors[6] will provide capabilities at the mist-computing level that are hard to grasp in the current market – just like the smartphone was hard to grasp in the earlier cell phone market.

The best example for understanding future architectures is to look at the vehicle-tovehicle (V2V) and vehicle-to-infrastructure (V2I) systems being rolled out now and for the coming decade. This infrastructure looks like the cloud, yet vehicles will communicate with each other and make mutual decisions without reference to the infrastructure. These are fog devices. Drilling further down into automotive systems, individual electronic control units in the car will also make decisions about their own subsystems without reference to the overall car system. This is mist computing – and it is already here. IoT References

The CRATUS Technology/ Fujitsu BlueBrain sensor platform contains a range of sensors and actuators toFIGURE 4 gether with a microcontroller, communications, and firmware framework. It is used to create rapid proofs-ofSEA-18026 - IoT Design.pdf 1 concept for IoT applications.

www.embedded-computing.com/iot

1. “Internet of Things leaders create Open Fog Consortium to help enable end-to-end technology scenarios for the Internet of Things.” 2015, November 19. https://iotbusinessnews. com/2015/11/19/80306-internet-of-things-leaders-create-openfog-consortium-to-helpenable-end-to-end-technology-scenarios-for-the-internet-of-things/.

2. McMillin, Bruce, et al. “Fog computing for smart living.” 2017, February. IEEE Computer Magazine, Vol 50, No 2, page 5.

3. Wald, Matthew L. “For no signs of trouble, kill the alarm.” 2010, July 31. New York Times. http://www.nytimes.com/2010/08/01/weekinreview/01wald.html.

4. “FUJITSU Component sensor-based system BlueBrain interface board.” 2017, August 2. http://www.fujitsu.com/downloads/MICRO/fcai/wireless-modules/bluebrain-interfaceboard.pdf.

5. Markakis, Evangelos K., et al.. “EXEGESIS: Extreme edge resource harvesting for a virtualized fog environment.” 2017, July. IEEE Communications Magazine, pp 173-179.

6. Gunay, Z. “Software-defined sensors for Industrial IoT and Industrie 4.0.” 2017, October 31. www.cratustech.com/downloads/.

Brian MacLeod is Vice President of Marketing and Business Development at Inc.

3/20/18 9:50 Technology, AM CRATUS

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WIRELESS Firmware CHIPSETS Updates

Bluetooth 5 and Bluetooth mesh: Enabling use cases for Industry 4.0

By Pelle Svensson, u-blox

In December 2016, the Bluetooth Special Interest Group (SIG) rolled out Bluetooth 5, the latest version of the Bluetooth core specification. This fifth revision included a number of groundbreaking enhancements.

In June 2017, the SIG released the spec for Bluetooth mesh, which is a software enhancement that can run on any Bluetooth Low Energy (BLE) solution; it does not require Bluetooth 5.

The features provided by Bluetooth 5 and Bluetooth mesh are the most substantial enhancements to Bluetooth technology since its introduction in 1998. They will enable a host of new use cases, some of which are of specifically relevant to Industrial IoT (IIoT) applications.

Bluetooth 5 provides three main feature improvements compared to the preceding release: double the data rate (from 1 to 2 Mbps), four times the range, and eight times the advertising packet size (beacons). While sending data using Bluetooth 5 draws slightly more power than previously, transmission times are cut in half. As a result, the same amount of data can be sent with just over 50 perc-ent of the total power required by Bluetooth 4.2 (Figure 1). In addition to faster data transmission rates, shorter transmission times result in improved coexistence with other 2.4-GHz radios

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(including other BLE connections), as the radio is active for a shorter duration.

Extended range

20 dBm compared to today’s 10 dBm. This enables even greater distances between Bluetooth 5 devices, of course at the cost of increased power consumption.

By extending the range of Bluetooth signals, the Bluetooth SIG is seeking to extend the reach of BLE to cover entire homes. Two new modulation options, 125 Kbps and 500 Kbps, potentially offer a 4x range improvement compared to the current BLE specification. In line-of-sight, the range of Bluetooth signals is expected to exceed 1 km using the same amount of power. The Bluetooth 5 spec further increases maximum output power to

Home automation is obviously a key target application for the Bluetooth SIG going forward, clearly indicated by the fact that two new members of the Bluetooth SIG board of directors were brought in from Philips Lighting and Google Nest. Key players in the home automation industry see an interest in adopting BLE to connect the devices they develop. www.embedded-computing.com/iot

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Richer beacons The third new feature Bluetooth 5 brings to the table is extended advertising capability. First introduced in BLE, advertising lets low-power sensor nodes signal “I have new data” to a central unit. If the central device is interested in that data, it initiates a connection during which it exchanges data with the sensor node. Once the exchange is completed, the connection is closed and the sensor node goes back into low power mode.

Short advertising messages were sufficient to enable this type of exchange.

However, it didn’t take long for device makers to figure out that this kind of “non-connected” advertising message can also be used as a beacon to broadcast information without first having to establish a connection. Apple developed their way of doing it in iBeacon, and Google countered with Eddystone.

With the popularity of the beacon use case came the desire to make it more powerful and broaden its scope.

Bluetooth 5 takes the beacon use case to a new level by increasing advertising message length from 31 bytes to 512 bytes, even allowing for multiple 512-byte messages to be linked together. To avoid congestion, it extends these longer advertising packets to all 40 available channels rather than limiting advertising to three channels as in the previous specification.

Extended advertising capability lets nodes send more data packets, even packet streams, without first having to establish a BLE connection. Even though BLE was designed for low-power use cases, short data packets, and quick connection establishment, establishing a BLE connection always consumes extra power. In some use cases, broadcasting data connection-free can push down total power consumption even further.

Bluetooth mesh Shortly after the release of the Bluetooth 5 spec, the SIG released the specification for Bluetooth mesh. Together, Bluetooth 5 and Bluetooth mesh lay the foundation for many new applications and use cases. www.embedded-computing.com/iot

FIGURE 1

Power consumption of a Bluetooth 5 2 Mbps PHY.

FIGURE 2

The Bluetooth mesh usage model: Publish and subscribe.

They’re particularly important for the IIoT as they enable use cases previously only possible with technologies like ZigBee, Sub-GHz, etc.

Because Bluetooth mesh is standardized by the Bluetooth SIG, devices implementing it will be interoperable. Bluetooth mesh is designed around a publish-subscribe model, managed flooding, and friendship for low-power nodes.

In a Bluetooth mesh network, network nodes are configured to operate in a publishsubscribe model. Information among nodes is transmitted in messages. Nodes providing data or actions use messages to publish information on the network. Other nodes can either collect the data in messages or use it for actions. Figure 2 depicts a simple mesh network made up of switches and lights and shows how they are configured to operate.

To spread a message across the mesh, the source node simply broadcasts its message using advertising. Other nodes in the network then receive and forward the message to all other nodes, extending the range of the mesh network well beyond the capability IoT Design Guide 2018

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Wireless Chipsets of an individual Bluetooth link. This is known as a flooding mesh. There are several basic mechanisms in place to ensure that the network is not overloaded.

Examples include not relaying messages that a node has already touched, and limiting the number of hops.

For a network to support relaying, relaying nodes must actively listen to messages all the time. This means that they can’t operate in low-power mode.

Nodes with limited power can instead be configured in a friendship relationship with relaying nodes. In a friendship relationship, the relaying node temporarily stores data until the low-power node wakes up (Figure 3). Then the data is exchanged during the short period in which the low power node is active.

FIGURE 3

Low power nodes in friendship with relaying nodes.

FIGURE 4

BLE data rates support firmware upgrades over the air.

Industry 4.0 Industry 4.0, sometimes used synonymously with the IIoT, is an initiative that was launched by the German government in 2011. Since then, many other regions have created their own variants of the concept. In 2015, Japanese companies formed the Industrial Value Chain Initiative (IVI). In the US, the Industrial Internet Consortium (IIC) was set up to encourage greater use of the Internet in the American manufacturing sector.

In manufacturing, Industry 4.0 seeks to leverage technology to improve efficiency and reduce impact on natural resources. Examples of such enabling technologies include low-power and low-cost sensors, wireless connectivity, affordable network infrastructure, and computing power to analyze the large amount of collected data (big data).

In predictive maintenance applications, for example, sensors are added to traditional electric motors. Sensor data is then analyzed to assess their operation (temperature, vibrations, etc.) and predict when maintenance becomes necessary.

The objective of predictive maintenance is to prevent unexpected failures that would cause unplanned disruptions in the manufacturing process, but also to avoid unnecessary maintenance operations imposed by an overly conservative preventive maintenance schedule.

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Bluetooth 5 in Industry 4.0 The enhanced features provided by Bluetooth 5 pave the way for a number of new IIoT applications. Examples include device firmware upgrades, large industrial sensor networks, asset tracking, connected buildings, and industrial real-time control. The increased data rate provided by Bluetooth 5, up to 1.4 Mbps, is sufficient to quickly send small files over a BLE connection. This makes it possible for industrial devices running embedded firmware, such as variable-frequency drives, to use a BLE connection to transfer firmware files for device firmware upgrades over the air (DFU-OTA) as shown in Figure 4. In fact, the latest generation of smartphones that support Bluetooth 5 may be used as mobile gateways between the Internet and the industrial device.

With a data rate of 1.4 Mbps, it only takes seven seconds to send a 1 Mb firmware file, which is typical in many embedded industrial products. Device manufacturers might even consider replacing Wi-Fi with BLE for this use case, bringing down both device cost and power consumption.

IIoT capillary sensor networks In the predictive maintenance use case, sensors need to be connected to a number of otherwise unconnected devices. There are two ways to do this: sensors can either connect directly to the cellular network, or they can connect to short-range radio networks that, in turn, are connected to cellular gateways. The second approach is referred to as a capillary sensor network (Figure 5).

Bluetooth 5 and Bluetooth mesh can support capillary sensor networks by letting large numbers of sensors connect into a large network. Using Bluetooth as the short-range radio has multiple advantages over other short-range technologies. The main one is that Bluetooth is supported in almost all smartphones and tablets, making them the obvious tools for sensor and network configuration. www.embedded-computing.com/iot

the network can then be used to determine the approximate location of each asset. The accuracy provided is sufficient to know on what floor and in which room valuable assets are located. Examples of assets that could be monitored using this approach are expensive, moveable industrial equipment and specialized tools at manufacturing sites.

Industrial-strength connections

Asset tracking

While Bluetooth began its existence primarily as a consumer technology, recent enhancements in version 5 of the Bluetooth specification broaden the technology’s horizons into new markets and applications. Cost and powersensitive IIoT systems now have a viable alternative for short-range wireless communications backed by an ecosystem that will ensure its longevity. IoT

Mesh networks set up to control lighting in a building or factory, for example, can be used to enable additional use cases such as asset tracking. This requires configuring Bluetooth-mesh-enabled asset tags to connect to the same mesh network, allowing nodes in the mesh sensor network to report which asset tags they detect back to devices monitoring the network. Information gathered from several nodes in

Pelle Svensson is a product marketing manager in the u-blox product center for short-range radio modules, based in Malmo, Sweden.

FIGURE 5

Capillary networks according to Ericsson.

OpenSystems Media E-cast Five ways to improve reliability in IIoT systems Sponsored by RTI Industrial Internet of Things (IIoT) applications are extremely complex and require sharing data across hybrid networks on the edge, in the fog, and to the cloud.

Reliability in these systems is a challenging yet critical requirement. In this webinar, learn five specific ways to improve the inherent reliability of your next IIoT application using the layered databus architecture pattern.

ecast.opensystemsmedia.com/796 www.embedded-computing.com/iot

IoT Design Guide 2018

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WIRELESS CHIPSETS

Beyond the Bluetooth beacon: Why today’s application requirements have moved beyond what beacons can offer

By Fabio Belloni, Quuppa

As the need for companies to understand the location of a person or thing grows, a conversation about potential indoor solutions inevitably starts with Bluetooth beacons. A well-known and simple system for indoor applications such as retail customer engagement or general warehouse localization, Bluetooth beacons are based on a network of Bluetooth Low Energy (BLE) chips set in specific locations that transmit a unique signal.

Smartphones in the area can receive these signals, determine the beacon’s location based on signal strength, and use the information from several beacons to estimate the location of the smartphone.

Barriers for Bluetooth beacons While the simplicity of Bluetooth beacons is appealing for certain applications, in many cases they’re too simplistic. First off, Bluetooth beacons can only be used with smartphones, not tags, and as such are not applicable in applications such as asset or people tracking based on ID badges. Furthermore, while beacons generally provide accuracy within 3-4 meters, they simply aren’t precise enough for applications where more than proximity is required. For example, beacons might be able to determine the location of a smartphone in a mall, but not whether a user is in front of the coffee shop or the shoe store. As such, even a basic welcome messages or advertising specials can be delivered incorrectly.

Bluetooth beacons can also be challenging from an operational perspective. Beacons are, of course, mainly battery-operated devices, and one of their key selling points is their untethered nature. They’re easy and relatively cheap to install. However, this requires constant maintenance, making beacons less cost-effective over time. In large deployments such as an airport, shopping mall, or even large retail store, a large number of beacons will be required for reasonable location accuracy, highlighting the complexity of this challenge. Battery performance depends on a number of factors, including settings, environment, power modes, and rules that establish how often beacons transmit a signal. These variables could result in beacons having a battery life

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of only a few months, resulting in operational expenses that frequently ruin the business case.

Batteries can also impact the real-time nature of location services required by many devices. Bluetooth beacons only transmit periodically because real-time location drains battery life. For example, navigation applications cannot function with more than a 1 to 2 second delay in location updates. Otherwise the app will say “you should have turned right” instead of “turn right.”

Beyond Bluetooth beacons So, if Bluetooth beacons aren’t enough for emerging applications, what can provide higher, more reliable, real-time accuracy? www.embedded-computing.com/iot

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The world of IoT is very much about tracking mobile assets. Smartphonecentric beacons are therefore giving way to network-centric systems built from “smart” receiver antennas. In configurations such as these, intelligence is located in the receiver antenna and a centralized software application rather than a smartphone app, allowing the devices being tracked (or located) to be much simpler. This opens up the possibility of using a wide range of low-cost tags with extremely long battery life. For systems that involve tracking hundreds, thousands, or hundreds of thousands of assets, the cost and life expectancy of such tags is crucial.

New approaches to angle estimation A network-centric solution enables the launch of active, low-cost BLE tags with extremely long battery-life, but also alters the way signals are measured to determine location.

As mentioned, signal strength has been used as the primary mechanism for estimating a device’s location in traditional Bluetooth beacon deployments, which fails to consider the impact of the physical environment such as a building’s layout or concrete walls. Therefore, if distance is derived from signal power and the power is affected by fading, the signal strength cannot be an accurate representation of physical distance.

This has resulted in new ways of thinking about how location is calculated within the Bluetooth Special Interest Group (BT SIG), and the organization has begun work on a new standard for BLE angle estimation based on two new approaches: 1. The first uses the signal’s angle of arrival (AoA), which is the exact direction the device is from the receiver antenna arrays.

AoA receivers utilize multiple antennas within the same device to better measure the signal, allowing antennas to locate a smartphone or tag to within www.embedded-computing.com/iot

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10-20 cm. This is about 20 times more accurate than most Bluetooth beacon systems. Location is also calculated much more quickly using AoA than beacons, because variations in signal strength require beacon-based systems to average readings over several seconds to achieve good results. Suddenly, applications that demand accurate real-time location capabilities – such as user navigation and collision avoidance services between machinery and people in a warehouse setting – are possible.

2. The second approach moves location intelligence back to smartphones and mobile devices when it makes sense for the application. These smart devices measure the “direction of departure,” or DoD. This works much like the AoA network-centric approach, and can measure locations of many more devices since the work is done on the device itself.

Next-generation precision location These innovative new approaches deliver a real-time, accurate location methodology that moves well beyond Bluetooth beacons and into the next generation of indoor location technology. This, in turn, will spawn even more industries that benefit from the abilities of precision location. IoT Fabio Belloni is general manager and co-founder of Quuppa LLC. Belloni has worked for the Nokia Research Center as senior researcher and principal researcher focusing on advanced algorithm development and antenna modeling, positioning technologies, hybrid systems architectures, indoor mapping, and navigation. He received a MS in Telecommunications Engineering from Politecnico di Milano, and a PhD from the Helsinki University of Technology (now part of Aalto University) Department of Electrical and Communications Engineering.

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SECURITY & DEVICE MANAGEMENT

UEFI: Firmware security for IoT devices

By Dick Wilkins, UEFI Forum, Phoenix Technologies, Ltd., and Thomas College

Over the past several years, the IoT has been touted as the “Next Big Thing,” as well as the “Internet of Crappy Things.” Both descriptions are justifiable. Poorly protected IoT devices have been used in numerous Distributed Denial of Service (DDoS) attacks, and supposedly helpful and friendly devices have invaded the privacy and exposed the personal information of their users.

I am concerned that developers are not paying enough attention to what the traditional computing industry has discovered the hard way. This article is focused on system startup/firmware and the potential security problems for IoT devices in that space. And, most important, what to do about them.

Many in the IoT ecosystem seem to consider their devices as simple, singleuse, throwaway devices, such as a basic appliance or embedded system that you ship and forget. This perception is problematic, as more and more IoT devices continue to be developed.

•• By definition, IoT devices are Internet-connected. That means a network stack, communications protocol, and applications on the device or in the cloud can take advantage of the data made available by the device. This connectivity also makes these devices desirable targets, and any security flaws open the door for attackers.

•• Due to the complexity and scope of IoT devices, in most cases they must be updateable in the field. The number of these devices and their usage model drives automatic and remote update capability, which provides another attack vector for those who would change device software to alter system behavior.

Such attack vectors are not a new phenomenon. Network-connected computer systems have been dealing with them since the advent of the Internet.

The problem has been that developers of IoT devices have seen their gadgets as simple, single-purpose devices that are not susceptible to nefarious acts, and therefore, not easily attackable.

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Well, it turns out the opposite is true. The bad guys can either steal user’s data, use the device to spy on the network infrastructure inside the user’s firewall, or use the device as a launch platform for attacks on other systems.

What to do about it It has been shown that if an attacker can get control of a system during the system startup and boot process, they can completely “own” what happens with that system. Ultimately, attackers can then disable protections provided in the software after boot-up and load whatever other programs they so choose. Additionally, they can modify normal software to do their bidding before it has even been started.

If the bad guys can get control of the system early enough, that system can be compromised entirely.

The same is true if the code update process is compromised. If a hacker creates their own code and swaps it with the code originally provided by the system manufacturer, then all the bad things listed previously can also be accomplished in a system with a compromised system update.

Fundamentally, the software/firmware of IoT devices must be protected in the same way code must be protected in general-purpose computer systems. This includes the firmware and software that initializes the device’s hardware, loads and starts up the device’s software (system and application), as well as the process in which the IoT device’s firmware and software are updated.

Platform firmware and startup security Since the early days of computing, platform firmware has been created to initialize the system hardware and load the initial software. For traditional computing platforms, this software was typically an operating system loaded from a disk, but even on embedded platforms without a traditional operating system, software is typically loaded from slow non-volatile storage into faster RAM memory for normal operations.

When IBM created their PCs, they developed firmware called the basic input/output system (BIOS) for this task. The original BIOS was cloned and used across many platforms; however, as computing systems became more complex, and it became difficult for processors to emulate the behavior of 1970’s PCs, a new standard was born. While simple embedded systems moved to monolithic solutions like U-Boot and coreboot, most larger and general-purpose systems looked to the Unified Extensible Firmware Interface (UEFI) standard. www.embedded-computing.com/iot

URL

www.uefi.org

LINKEDIN

www.linkedin.com/groups/1510977

The EFI design was initially created by Intel for a new generation of processors and eliminated most of the architectural limitations of BIOS. Intel tried to socialize EFI as general replacement for BIOS across the industry, but because it was “owned” by a single major industry player there was some resistance to the idea. Instead, Intel contributed the design to the industry and helped found the UEFI Forum to manage the architecture going forward. Today, the UEFI Forum is made up of over 300 companies and is responsible for the development and evolution of UEFI standards.

One of the initiatives taken on by the UEFI Forum has been the security of systems as they start up, as well as when their firmware/software inevitably needs to be updated. The UEFI specification provides standard interface descriptions and an architecture designed to significantly limit the aforementioned threats.

The two primary technologies used to secure a system from these threats are:

•• Secure Boot requires that all software components of a system be cryptographically signed or they will not be allowed to run. This prevents compromised components from running during system startup, which maintains a root-of-trust that can be continued all the way to the application software itself.

•• Capsule updates require that all system updates be cryptographically signed and provides facilities to ensure that the system firmware/ software cannot be rolled back to a less secure version.

UEFI is the only firmware solution that includes these security features as part of its industry standard. Also, while many security researchers and hackers have been testing its design, no one has been able to find any flaws in the security architecture. A few implementations have been flawed, but not the design.

There are many more security-related capabilities provided by UEFI, but they are beyond the scope of this article.

Refer to www.uefi.org for specifications, white papers, and training materials. www.embedded-computing.com/iot

GOOGLE+

plus.google.com/+UEFIForum

YouTube

www.youtube.com/user/UEFIForum

So why isn’t everyone using UEFI firmware?

If the UEFI architecture provides the “solution” to these security threats, why isn’t everyone using it? There are a couple of major reasons:

•• Many IoT developers come from the embedded space, where monolithic boot solutions are prevalent. Despite the limitations of solutions like U-Boot and coreboot, developers tend to use what they know and are comfortable with.

•• There are a number of misconceptions and “alternative facts” about UEFI firmware that limit its acceptance in certain communities. Examples of these misconceptions include: it is too slow; it is too big; the architecture is too complex; it is not “open;” etc. These are largely debunked in a white paper entitled “Clarifying the ten most common misconceptions about UEFI.”

Where do I go from here?

I hope this has convinced you to at least consider UEFI as a firmware design alternative for your next IoT device. So, how do you get started?

Downloading the latest UEFI specification and trying to read it cover to cover is probably not the best way to start. First, UEFI is an interface specification, not an implementation. The specification supports many capabilities that you probably will not need in your device, and the size of the specification can seem daunting at first glance (2000+ pages!). Only a handful of basic capabilities are required to be compliant with the specification, and you can pick and choose from the others based on your needs.

There are many educational materials, books, and presentations on the UEFI website.

As an interface specification, it does not drive the actual code implementation of the services described. There is an open-source example implementation available at Tianocore.org, along with decent documentation, which includes full implementations for several Intel reference platforms as well as code that may be used to create solutions for other platforms. There are also bindings for Arm processors and platforms, and the Arm folks have provided a document describing the requirements for UEFI on Arm-based devices. I have even heard that there are implementations of the UEFI interfaces layered on an underlying coreboot code base. It is completely up to you what your implementation looks like and what capabilities are needed.

There are several independent firmware vendors who would be happy to help you create a custom UEFI implementation just for your device.

Bottom line IoT devices are true network-connected computing devices with all the attendant risks. An IoT device with weak security not only risks the device itself and its data, but other devices in the local network and the Internet at large. As creators of these devices address their obvious security limitations, the bad guys will look for other attack vectors. These attack surfaces will include attacking device firmware and software update mechanisms. To keep your customers and other stakeholders happy, you owe it to yourself to consider a UEFI implementation for your IoT device. IoT Dr. Richard ‘Dick’ Wilkins is an Associate Professor of Computer Science at Thomas College in central Maine and is Principal Technology Liaison for Phoenix Technologies. He holds a Ph.D. in Computer Science from Nova Southeastern University, Ft. Lauderdale FL; a Masters of Science in Computer Science from the National Technological University, Ft. Collins, CO; and a Bachelor of Arts in Public Administration from Saint Thomas University, Miami, FL. Thomas College • www.thomas.edu Phoenix Technologies, Ltd. • www.phoenix.com IoT Design Guide 2018

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IOT CLOUD PLATFORMS

Hybrid IoT platforms deliver simplicity, flexibility, and fast time to market for the Internet of Things Terrence Barr, Electric Imp

The value of connected products and services is driven by IoT business applications, which in turn depend on trustworthy, accurate, and reliable data from devices in the field. Therefore, any IoT solution must be created and delivered end-to-end (from the device to the business application) to generate the expected business benefits.

However, implementing, deploying, and supporting end-to-end IoT solutions can be complex – in particular meeting the increasing commercial or industrial requirements for security, reliability, scalability, and longevity is challenging. This complexity is slowing down or preventing many IoT deployments today. Among some of the technical challenges are:

•• Security (from device hardware through communications to cloud and management) •• Hardware selection and product design •• Software complexity (device and cloud) •• Multitude of communications technologies •• Device manufacturing and deployment at scale •• Integration of legacy systems •• Protocol conversion and data integration •• Cloud infrastructure and scalability

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Many products and services companies do not possess the technical expertise, resources, or appetite for risk to build and deliver IoT solutions by themselves. For such companies, it makes more sense to focus on their core competencies and leverage IoT offerings from specialized vendors who abstract much of that complexity away from the customer.

Unfortunately, choosing the right IoT offerings itself is a challenge. A dizzying number of IoT offerings exist in the market today, from low-level device hardware components on one end to powerful cloud-based IoT platforms on the other end, and any number of components, technologies, standards, protocols, tools, and services in between.

When approaching the IoT solutions market, there are two extremes visible: 1. Bespoke IoT solutions – Custom solutions based on a number of different technology and service components, which are then assembled, integrated, delivered, and supported by a vendor for a specific customer 2. Off-the-shelf IoT solutions – Pre-integrated technology and services packaged as IoT solutions that target specific markets and use cases, which are offered by a vendor with limited customization Building bespoke IoT solutions from components offers maximum flexibility, but requires substantial expertise, incurs technology and execution risk, and carries the burden of having to support the bespoke IoT solution over its entire lifetime. From experience, this burden is almost always underestimated (especially with regards to security), resulting in projects going over time and over budget. www.embedded-computing.com/iot

www.electricimp.com

Off-the-shelf solutions focus on narrow functionality for specific applications and market segments, typically trading fast time-to-market and simplicity against flexibility. While off-the-shelf offerings may initially seem attractive, companies often find that these are not flexible enough to integrate well with existing products and business models; do not scale across product or business lines; and don’t evolve well with business needs. The difference between a proof of concept and a shipping IoT product is often about corner cases that occur in the real world, and a rigid IoT solution is often not capable of handling these corner cases efficiently.

Both extremes are not viable for the majority of the companies seeking IoT solutions today, as many are looking for a straightforward but flexible approach to IoT (Figure 1). The key business requirements of these organizations can be summarized as follows:

•• Fast time-to-market; low execution risk; and predictable, bounded expenditure •• Well-designed, fully integrated security from device hardware to cloud that is maintained for the lifetime of the product •• Flexibility to address unique and evolving technology and business needs •• Easy integration with, and support for, existing and future products •• Simplified procurement, integration, and delivery without sacrificing functionality or flexibility •• Low upfront investment and the ability to incrementally invest as connected business scales •• Cost effective, timely, long-term support for solutions

The alternative: A hybrid IoT platform approach One alternative that meets the aforementioned requirements is a hybrid IoT platform approach, which combines a comprehensive IoT device connectivity and management platform with the IoT application cloud platform best suited for the customer’s needs. (Figure 2) www.embedded-computing.com/iot

TWITTER

LINKEDIN

@electricimp

www.llinkedin.com/company/ electric-imp-inc-

YOU TUBE

GOOGLE PLUS

www.youtube.com/user/ ElectricImpVideo

https://plus.google.com/ 112599544511835212166

Bespoke

Solution Flexibility

Electric Imp

Bulk of IoT Solutions Market – How to address?

Off-the-Shelf

Solution Time to Market, Cost, Risk FIGURE 1

IoT solutions available on the market today are largely totally custom or off-the-shelf, creating flexibility and time to market tradeoffs for IoT companies.

Combining two domain platforms for a complete solution: Pre-integrated, tested, and validated Device Domain

Data/Application Domain

Data Integration Provisioning & OTA Updates Management & Scale Edge Processing Connectivity Device Security

Enterprise Orchestration Applications Analytics Processing Storage Data Ingestion

Device Connectivity & Management Platform

Data

IoT Application Cloud Platform

End-to-End Solution

FIGURE 2

Combining a device connectivity and management platform with a cloud application platform provides a balanced infrastructure that is flexible, can scale, and allows organizations to get to market quickly.

1. IoT device connectivity and management platform An IoT device connectivity and management platform connects devices to the cloud securely, reliably, and at scale. Device connectivity and management is a highly specialized field that requires expertise in device hardware, security from device to cloud and all layers in-between, robust bi-directional connectivity (data and control), device management, software provisioning and over-the-air (OTA) updates, protocol integration and data conversion, cloud integration, massive scalability, and more. The security, flexibility, and scale of an IoT device connectivity and management platform are prerequisites to getting trustworthy IoT data into the application cloud. Without trusted device data, there can be no IoT business value.

2. IoT application cloud platform The IoT application cloud platform provides massive-scale device data ingestion, processing and storage, business applications, and enterprise orchestration. IoT cloud platforms typically rely on external mechanisms to provide device security, connectivity, and management, which is where an IoT device connectivity and management IoT Design Guide 2018

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IoT Cloud Platforms

platform comes in. The ease and flexibility of integration between the two platforms is critically important for real-world IoT solutions, as it enables a vendor to optimize a complete solution to the customer’s requirements.

A hybrid IoT platform approach provides important benefits to companies looking to build IoT solutions, as it:

•• Strikes an optimal balance between flexibility and time-tomarket for many companies and their IoT use cases •• Leverages proven platform implementations for common IoT functionality while enabling customization of the IoT solution to meet the customer’s unique needs •• Simplifies procurement and support of the IoT solution with only two key vendors and well-defined responsibilities and integration points

•• Provides flexibility to evolve with the customer’s business needs, both on the device and on the cloud side, including expanding the solution with additional connectivity options and a wider range of cloud services

Closing thoughts Creating, deploying, and supporting device-to-cloud IoT business applications can be complex and challenging. Bespoke IoT solutions provide maximum flexibility but are costly, time consuming, and not a viable option for many companies. Off-the-shelf IoT solutions offer simplicity and fast time-to-market, but often lack the necessary flexibility to adapt and grow with business needs.

A hybrid IoT platform approach can deliver the best option for many companies by combining a comprehensive IoT device connectivity and management platform with the customer’s preferred IoT application cloud platform. This approach integrates two proven and ready-to-use platforms to deliver the necessary common IoT functionality while providing the flexibility to easily adapt and extend the IoT solution to emerging requirements.

The result is a customized device-to-cloud IoT solution that can be delivered to market quickly, with low risk, and evolve over time as the needs of a customer grow. This is what most companies need to successfully extend their core product and service business into the connected world of the Internet of Things. IoT

Terrence Barr is Head of Solutions Engineering at Electric Imp.

OpenSystems Media works with industry leaders to develop and publish content that educates our readers.

How IoT is transforming mass transit

By Cisco The many problems that mass transit must deal with cannot be solved by a piecemeal approach.

An end-to-end, connected IoT system gives managers the bird’s-eye view they’ve been missing. By combining data points from every part of a transit system – from vehicle location and condition to fuel efficiency, security, and passenger use – the IoT lets managers see the big picture and make changes that bring lasting results.

www.embedded-computing.com/white-paper-library/cisco-transforming-mass-transit-osm

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Check out our white papers at www.embedded-computing.com/ white-paper-library www.embedded-computing.com/iot

BY ENGINEERS, FOR ENGINEERS In the rapidly changing technology universe, embedded designers might be looking for an elusive component to eliminate noise, or they might want low-cost debugging tools to reduce the hours spent locating that last software bug. Embedded design is all about defining and controlling these details sufficiently to produce the desired result within budget and on schedule.

Embedded Computing Design (ECD) is the go-to, trusted property for information regarding embedded design and development.

embedded-computing.com

IoT Design Guide

2018 DESIGN GUIDE PROFILE INDEX Page Advertiser

Category

30-32

Lauterbach, Inc. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Development Kits

32-33

Technologic Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Development Kits

33

EMAC, Inc. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Industrial

34

Advantech, Inc. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Industrial

35

Apacer Memory America, Inc. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Industrial

36 Virtium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Industrial 37

WinSystems, Inc. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Industrial

38

Fujitsu Components America . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Industrial

38

EMAC, Inc. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NB-IOT

39

Fujitsu Components America . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wireless

39

PathPartner Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wireless

Development Kits

TRACE32 Multi Core Debugger for TriCore Aurix Lauterbach TriCore debug support at a glance: For more than 15 years Lauterbach has been supporting the latest TriCore microcontrollers. Our tool chain offers: • Single and multi core debugging for up to 6 TriCore cores • Debugging of all auxiliary controllers such as GTM, SCR, HSM and PCP • Multi core tracing via MCDS on-chip trace or via high-speed serial AGBT interface The Lauterbach Debugger for TriCore provides high-speed access to the target application via the JTAG or DAP protocol. Debug features range from simple Step/Go/Break up to AutoSAR OS-aware debugging. High speed flash programming performance of up to 340kB/sec on TriCore devices and intuitive access to all peripheral modules is included.

Lauterbach’s TRACE32 debugger allows concurrent debugging of all TrCore cores.

• Cores can be started and stopped synchronously.

• The state of all cores can be displayed side by side.

• All cores can be controlled by a single script.

Lauterbach, Inc.

www.lauterbach.com

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FEATURES ĄĄ Debugging of all auxiliary controllers: PCP, GTM, HSM and SCR ĄĄ Debug Access via JTAG and DAP ĄĄ AGBT High-speed serial trace for Emulation Devices ĄĄ On-chip trace for Emulation Devices ĄĄ Debug and trace through Reset ĄĄ Multicore debugging and tracing ĄĄ Cache analysis iotdesign.embedded-computing.com/p374253

 info_us@lauterbach.com  508-303-6812 www.lauterbach.com/pro/pro_tc3xx_aurix_as_alt1.php?chip=TC399XE%20A-STEP

www.embedded-computing.com/iot

Lauterbach Debugger for Intel x86/x64 Skylake/Kabylake Lauterbach TRACE32 Debugger for Intel x86/x64: In January of this year, Lauterbach introduced the new CombiProbe Whisker MIPI60-Cv2. The TRACE32 CombiProbe and TRACE32 QuadProbe now offer the same debug features for the Converged Intel® MIPI60 connector: • Standard JTAG, Intel® debug hooks with Pmode, and I2C bus • Merged debug ports (two JTAG chains) • Intel® Survivability features (threshold, slew rate, ...)

However, these debug tools have different areas of application. The TRACE32 QuadProbe, which is expressly designed for server processors, is a dedicated debug tool that enables SMP debugging of hundreds of threads on targets with up to four debug connectors.

The TRACE32 CombiProbe with the MIPI60-Cv2 Whisker, designed for client as well as mobile device processors, can capture and evaluate system trace data in addition to its enhanced debugging features.

Trace capabilities include support of one 4-bit and one 8-bit trace port with nominal bandwidth.

The TRACE32 CombiProbe with the DCI OOB Whisker is specially designed for debugging and tracing of form factor devices without debug connectors. If the chip contains a DCI Manager, the target and the debugger can exchange debug and trace messages directly via the USB3 interface. The DCI protocol used to exchange messages supports standard JTAG and Intel® debug hooks as well as trace messages for recording system trace information.

FEATURES ĄĄ

ĄĄ ĄĄ

ĄĄ

ĄĄ

CombiProbe MIPI60-Cv2 provides debug and system trace capability Support for standard JTAG, debug HOOKs and I2C bus Support for merged debug ports (two JTAG chains per debug connector) Support for survivability features (threshold, slew rate, etc.)

Support for system trace port with up to 8 trace data channels

ĄĄ

128 MByte of trace memory

ĄĄ

SMP debugging (including hyperthreading)

ĄĄ

AMP debugging with other architectures

ĄĄ

BIOS/UEFI debugging with tailor-made GUI for all UEFI phases

ĄĄ

Linux- and Windows-aware debugging

ĄĄ

Hypervisor debugging

iotdesign.embedded-computing.com/p374255

Lauterbach, Inc.

www.lauterbach.com www.embedded-computing.com/iot

info_us@lauterbach.com  508-303-6812 www.lauterbach.com/pro/pro_core_alt1.php?chip=COREI7-7THGEN



IoT Design Guide 2018

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IoT Design Guide

Development Kits

IoT Design Guide

Development Kits

Lauterbach Debugger for RH850 Lauterbach RH850 debug support at a glance: The Lauterbach Debugger for RH850 provides high-speed access to the target processor via the JTAG/LPD4/LPD1 interface. Debugging features range from simple Step/Go/Break to multi core debugging. Customers value the performance of high speed flash programming and intuitive access to all of the peripheral modules.

TRACE32 allows concurrent debugging of all RH850 cores.

• The cores can be started and stopped synchronously.

• The state of all cores can be displayed side by side.

• All cores can be controlled by a single script.

All RH850 emulation devices include a Nexus trace module which enables multi core tracing of program flow and data transactions. Depending on the device, trace data is routed to one of the following destinations: • An on-chip trace buffer (typically 32KB) • An off-chip parallel Nexus port for program flow and data tracing • A high bandwidth off-chip Aurora Nexus port for extensive data tracing The off-chip trace solutions can store up to 4GB of trace data and also provide the ability to stream the data to the host for long-term tracing, thus enabling effortless performance profiling and qualification (e.g. code coverage).

Lauterbach, Inc.

www.lauterbach.com

FEATURES ĄĄ AMP and SMP debugging for RH850, GTM and ICU-M cores ĄĄ Multicore tracing ĄĄ On-chip and off-chip trace support ĄĄ Statistical performance analysis ĄĄ Non intrusive trace based performance analysis ĄĄ Full support for all on-chip breakpoints and trigger features ĄĄ AUTOSAR debugging iotdesign.embedded-computing.com/p374254

 info_us@lauterbach.com  508-303-6812 www.lauterbach.com/pro/pro_r7f701325_alt1.php?chip=R7F701334A

Development Kits

TS-7553-V2 The TS-7553-V2 is developed around the NXP i.MX6 UltraLite, operating at speeds up to 696 MHz. While able to support a wide range of embedded applications, the TS-7553-V2 was specifically designed to target the Industrial Internet of Things sector.

The TS-7553-V2 was designed with connectivity in mind. An on-board interface, capable of supporting Xbee or NimbleLink, provides a simple path to adding a variety of Wireless interfaces. An Xbee radio can be used to link in with a local 2.4GHz or sub 1 GHz mesh networks, allowing for gateway or node deployments. Digi and NimbleLink offer cellular radios for this socket, providing connectivity for applications such as remote equipment monitoring and control. This allows transmission of serial data via TCP, UDP or SMS over the cellular network. The TS-7553-V2 also includes onboard WiFi and Bluetooth.

Further radio expansion can be accomplished with the two internal USB interfaces via a dongle or USB connected device. This provides the opportunity to run mesh, LoRa, ZigBee, automotive WiFi or other protocols with the TS-7553-V2. All of these radio options, combined with the on-board 10/100Base-T Ethernet, create the opportunity to communicate seamlessly with up to five different networks simultaneously from a single point.

Technologic Systems

www.embeddedarm.com

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FEATURES ĄĄ NXP i.MX6UL 698MHz ARM Cortex-A7 CPU ĄĄ 512 MB DDR3 RAM

ĄĄ 4 GB MLC eMMC Flash

ĄĄ XBee/NimbeLink socket

ĄĄ WiFi/Bluetooth radio on-board

ĄĄ USB host and device ports, Ethernet, and serial ports ĄĄ Industrial temperature range of -40 °C to 85 °C

iotdesign.embedded-computing.com/p374424 



sales@embeddedARM.com @ts_embedded

 480-837-5200

www.embedded-computing.com/iot

TS-4900 Computer on Module The TS-4900 is a high performance Computer on Module based on the NXP i.MX6 CPU which implements the ARM® Cortex™-A9 architecture clocked at 1 GHz (Single or Quad Core) and paired with 1GB or 2GB of DDR3 RAM. Several industry standard interfaces and connections such as Gigabit Ethernet, WiFi and Bluetooth, USB, SATA II, PCI Express, and more make the TS-4900 a great fit for nearly any embedded systems application, especially those needing wireless connections like an industrial internet of things gateway. A wide variety of software platforms are available including Linux, Ubuntu Core, Android, Windows Embedded Compact 2013, and QNX for flexibility in matching your embedded system requirements.

FEATURES ĄĄ 1 GHz Single or Quad Core Cortex A9 ARM CPU ĄĄ 2 GB DDR3 RAM

ĄĄ Bluetooth and WiFi onboard radios ĄĄ 4GB MLC eMMC flash storage ĄĄ microSD card socket

ĄĄ 7x COM (TTL), 2x RS-485 (Transceiver Required) ĄĄ Up to 70x DIO, 2x I2C, 1x I2S, 2x SPI, 2x CAN

iotdesign.embedded-computing.com/p374564

Technologic Systems

www.embeddedarm.com



sales@embeddedARM.com

 @ts_embedded

 480-837-5200

Industrial

SoM-iMX6U UltraLite ARM System on Module Designed and manufactured in the USA, the SoM-iMX6U is an ultra-low power ARM System on Module (SoM) designed to plug into an EMAC carrier board that contains all the connectors and I/O required or Customer designed for a system. The SoM-iMX6U is based on the Freescale/NXP i.MX6 UltraLite Cortex-A7 processor.

A SoM is a small embedded module that contains the core of a microprocessor system. The SoM-iMX6U is an industrial temperature, ultra-low power 528 MHz module with 4GB of eMMC Flash, 8MB of serial data flash, and 512MB of LP DDR2 RAM. The module has 10/100 BaseT Ethernet, 4x serial ports, GPIO & A/D. The recommended development/carrier board is the SoM-150 carrier board.

Pricing as low as $65.

EMAC, Inc.

www.emacinc.com/products/system_on_module/SoM-IMX6U www.embedded-computing.com/iot

FEATURES ĄĄ Freescale/NXP i.MX6 UltraLite (MCIMX6G1) Cortex A7 528Mhz ĄĄ 512 MB of LP DDR2 RAM, 4 GB of eMMC Flash, 8MB of Serial

Data Flash ĄĄ 1x 10/100 BaseT Ethernet 1x SPI, 1x I2C, 1x I2S & 1x CAN ĄĄ 22x GPIO, 2x USB 2.0 High Speed Host, 1x USB 2.0 High Speed OTG (Host Device) ports, 4x serial ports ĄĄ Industrial Temperature -40° to + 85° C ĄĄ APM ~5mA Sleep

iotdesign.embedded-computing.com/p373790 



info@emacinc.com  618-529-4525 www.linkedin.com/company/emac-inc-/

 @emac_inc

IoT Design Guide 2018

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Development Kits

IoT Design Guide

Industrial

Advantech LPWAN Edge Intelligence Server – EIS-D210 To fulfill customer requirements in equipment connectivity, data visualization, and predictive maintenance applications, Advantech offers the EIS-D210 Edge Intelligence Server, and is AWS Greengrass and Microsoft Azure IoT Edge certified (optional), thus ensuring that IoT devices can respond quickly to local events, interact with local resources, operate with intermittent connections, and minimize the cost of transmitting IoT data to the cloud. In addition to supporting field protocols (MQTT/OPC/Modbus) for sensor/ device data acquisition, the EIS-D210 can be used with the Advantech IoT SDK for wireless sensor (Wi-Fi, LoRa, Zigbee) data integration. Furthermore, the EIS-D210 comes pre-integrated with Advantech’s WISE-PaaS/EdgeSense software solution, allowing users to incorporate sensor data aggregation, edge analytics, and cloud applications for fast and easy real-time operational intelligence.

EIS-D210 provides a range of connectivity options with excellent data handling and networking connection capabilities for various IoT applications.

FEATURES ĄĄ

ĄĄ

ĄĄ

ĄĄ

ĄĄ

ĄĄ

ĄĄ

Integrated hardware plus software to build up edge-to-cloud applications Pre-configured system: Intel® Celeron® N3350 SoC, Win 10 Ent with 4GB Memory, 64 GB SSD and wireless networking Pre-integrated WISE-PaaS Software Package: WISE-PaaS/RMM, WISEPaaS/OTA, WISE-PaaS/Security, and WebAccess/SCADA Built-in Microsoft Azure IoT Edge and AWS Greengrass for cloud application Pre-configured Microsoft Azure service: Device Management Package/ Data Intelligence Package (Optional) Pre-configured AWS service: Connect & Collect Package (Optional) Comprehensive developer tools and documents: Node-RED data flow logic designer, dashboard builder, protocol plug-in SDK & configuration tools

For more details, or to get in contact with our IoT Sales Team, visit: www.advantechusa.com/eis-d210

iotdesign.embedded-computing.com/p374586

Advantech Corp.

www.advantech.com

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

IoTinfo@advantech.com

 www.linkedin.com/company/advantech/

 949-420-2500 @Advantech_USA



www.embedded-computing.com/iot

iotdesign.embedded-computing.com/p374589

Apacer Memory America, Inc. http://industrial.apacer.com www.embedded-computing.com/iot

 

Sales Inquiry: ssdsales@apacerus.com Tech Support: ssdfae@apacerus.com

IoT Design Guide 2018

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Industrial

IoT Design Guide

Industrial

®

Solid State Storage and Memory

Industrial-Embedded Solid State Storage and Memory Virtium manufactures solid state storage and memory for the world’s top industrial embedded OEM customers. We design, build and support our products in the USA, and provide a dedicated software team for custom storage solutions – all fortified by a network of global locations.

Our mission is to develop the most reliable storage and memory solutions with the greatest performance, consistency and longest product availability.

Industry Solutions include: Communications, Networking, Energy, Transportation, Industrial Automation, Medical and Video/Signage.

SSD Advantages include: SATA, PCIe, USB and legacy CF and PATA solutions in all popular formats and capacities.

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SSD classes include: • Good (MLC) at *1X endurance – 3-year warranty • Better (iMLC) at *7X endurance – 5-year warranty • Best (SLC) at *30X endurance – 5-year warranty

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* Endurance Baseline = one entire drive write per day (DWPD) for the entire warranty period.

Virtium‘s new vtView SSD Software is tailored for the industrial-embedded market and enables designers to analyze, quality and monitor SSDs to improve reliability and longevity.

Memory Advantages include: lowest profile in the market, monolithic components, first-to-market highest capacity Mini-DIMMs, 100% industrial-temperature-tested at -45 degrees to 85 degrees Centigrade; built with server-grade components, conformal coating and under-filled heat sinks.

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In business nearly two decades.

100% focus and dedication for the industrial embedded market.

Fully integrated hardware, firmware and software supported by industry’s strongest application engineering team.

Made in the USA following strict ISO processes.

Long and successful track record of servicing Tier-1 Industrial OEMs. Leading innovator in small-form-factor, high-capacity, high-density, high-reliability designs.

Broad product portfolio from latest technology to legacy designs.

High service level unmatched by competition.

Strategic supply continuity through partnerships with leading technology suppliers.

Long-term direct relationships with leading suppliers ensure on-time priority allocations and longer availability.

Worldwide Sales and FAE support and industry distribution.

iotdesign.embedded-computing.com/p373487

Virtium

www.virtium.com

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sales@virtium.com www.linkedin.com/company/virtium

 949-888-2444 @virtium

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www.embedded-computing.com/iot

PX1-C415 PPC/104 OneBank™ Intel® E3900 Single Board Computer with Dual Ethernet WinSystems’ PX1-C415 single board computer is a PC/104 form factor SBC with PCIe/104™ OneBank™ expansion and the latest generation Intel® Atom™ processor. Its small size, rugged design and extended temperature make it ideal for industrial IoT applications and embedded systems in industrial control, transportation, Mil/COTS, and energy markets.

Datasheet Link: www.winsystems.com/product/px1-c415/ Product Page Link: www.winsystems.com/wp-content/uploads/datasheets/px1-c415-ds.pdf

FEATURES ĄĄ Intel Atom E3900 Processor (Dual or Quad-core) ĄĄ Up to 8 GB DDR3-LV System RAM

ĄĄ -40°C to +85°C Operating Temperature Range

ĄĄ PC/104 Small Form Factor with PCIe/104™ OneBank™ ĄĄ Supports Multiple Simultaneous Displays

ĄĄ Secure and Trusted Data – ECC RAM, Intel Security Engine,

Cryptographic Acceleration

ĄĄ Connectivity and I/O for Embedded Systems ĄĄ USB Type C 3.0 and 8x USB 2.0 ĄĄ 24 GPIO with Event Sense ĄĄ Four Serial Ports

ĄĄ M.2 and SATA Expansion Options iotdesign.embedded-computing.com/p374588

SBC35-C398Q Quad-Core I.MX 6Q CORTEX®-A9 Industrial ARM® SBC

FEATURES ĄĄ Quad-core Freescale® i.MX 6Q Cortex A9 Industrial ARM CPU

@ 800 MHz

ĄĄ 2GB of Soldered DDR3 RAM

ĄĄ High-Performance Video and Graphics

ĄĄ Multiple Video Interfaces: HDMI 1.4, LVDS x2, and MIPI ĄĄ MIPI Capture/Display CMOS Camera Input ĄĄ Gigabit Ethernet with IEEE-1588™

WinSystems’ SBC35-C398Q quad-core single board computer combines high performance multimedia graphics with a rich mix of industrial I/O. The Freescale i.MX 6Q processor’s integrated power management provides excellent efficiency and allows operation from -40° to +85°C without active cooling. It is designed for demanding graphical applications in security, transportation, medical, and digital signage.

Datasheet Link: www.winsystems.com/product/sbc35-c398q-2-0/ Product Page Link: www.winsystems.com/wp-content/uploads/datasheets/sbc35-c398q-ds.pdf

ĄĄ Six USB 2.0 ports and one USB On-The-Go Port

We Specialize in Custom Embedded Solutions

ĄĄ Two CAN Bus ports, Five High Speed Serial ports ĄĄ 24 lines GPIO tolerant up to 30 VDC

ĄĄ CFast, SD/SDIO, and MicroSD sockets ĄĄ MiniPCIe and IO60 expansion

iotdesign.embedded-computing.com/p374427

ĄĄ Wide range DC or Power over Ethernet (PoE) PD Power Input

WinSystems, Inc.

www.winsystems.com www.embedded-computing.com/iot

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info@winsystems.com  817-274-7553 www.linkedin.com/company/1012196/

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BlueBrain® Sensor Based System The powerful BlueBrain® Sensor-Based System is a complete and intuitive, edge-processing platform with Bluetooth wireless capabilities for developing high-performance IIoT and automation applications. Using the BlueBrain platform and the capabilities of the Fujitsu integrated Bluetooth Low Energy module, OEMs can quickly accomplish proof of concept or prototype designs for wireless sensing devices running simple or complicated algorithms.

The BlueBrain platform includes a high-performance CORTEX-M4 microcontroller and embedded hardware interface board, software and industrystandard interfaces and peripherals. A portable Edge Processing Module features the Bluetooth wireless module to allow seamless data analysis from the sensor to the infrastructure. Simply attach it to a standard, 32-Pin 1.6" X 0.7" EEPROM-style IC socket, or equivalent footprint, on a mezzanine board to address specific markets and applications including industrial, agriculture, automotive and telematics, retail, smart buildings and civil infrastructure.

An available Development Breakout Board provides switch inputs and LED outputs for testing I/O ports and functions, as well as programming interfaces. It can be used in parallel with the Interface Board, which offers even more sensors and interfaces, to expand the development platform. A basic Android app is included to assist with application development.

FEATURES ĄĄ STM32F415RGT6 – ARM Cortex-M4 Main Controller ĄĄ MBH7BLZ07 – Fujitsu Components Bluetooth v4.1 (low energy)

Module With Cortex-M0 Controller

ĄĄ Flash (S25FL128SAGNFI001) 128Mb ĄĄ EEprom (24C16) 16Kb ĄĄ On Board Sensors: 3-Axis Accelerometer, Temperature Sensor ĄĄ Interfaces: USB, SPI, I2C, UART ĄĄ Mating Development Breakout Board and Interface Board iotdesign.embedded-computing.com/p374582

Fujitsu Components America

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www.fujitsu.com/downloads/MICRO/fcai/wireless-modules/bluebrain.pdf

components@us.fujitsu.com

 800-380-0059

 www.linkedin.com/company/fujitsu-components/

NB-IoT

CutiPy Industrial IoT Edge / Gateway Designed and manufactured in the USA the CutiPy™ Industrial IoT microcontroller was created to simplify connecting devices and machines to the multitude of systems you find in an industrial environment. EMAC Inc. has created an easy to use embedded solution that can be implemented anywhere from the factory floor to an offsite remote location. EMAC (Equipment Monitor And Control) designs, manufactures, integrates and distributes, Single Board Computers (SBCs), System on Modules (SoMs), Carrier Boards, Industrial Panel PCs (PPCs), Embedded Servers and Custom Solutions for the Embedded marketplace.

Since 1985, EMAC, Inc. has provided Off-The-Shelf and Custom turnkey OEM Embedded products utilizing the latest technologies. These technologies include Sensors, WiFi, Zigbee, Bluetooth LE, GPS, Cell Modems, Audio & Video streaming /capture, FPGA, RFID and more. Our team is experienced with Hardware & Software design, GUI interfaces, Remote Access, Real Time solutions, Windows Embedded, Embedded Linux, Custom Drivers, Application Development and Support.

Contact our Sales Team today at 618-529-4525 or info@emacinc.com and learn how “Our Products Make Your Products Better®”.

EMAC, Inc.

www.emacinc.com/products/pc_compatible_sbcs/IOT-F407C

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FEATURES ĄĄ STM32F407IGH6 ARM Cortex-M4, 168MHz with Math

Coprocessor, 192KB of SRAM, 1MB of Flash, microSD Card slot

ĄĄ Graphic 132x32 LCD with 4x pushbuttons & 4x LEDs, 1x Reset

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Button and 2x Dual Color Status LEDs, RTC with battery backup & temperature sensor 16x External Dedicated GPIOs (64x fully allocated), 4x Serial Ports, USB, SDIO, A/D, SPI, I2C & CAN. 2x 50 pin Female Expansion Connectors Zigbee, Thread, Bluetooth Low Energy & Wi-Fi -40 °C to +85 °C Industrial Temperature Power: 5Vdc, Dimensions: 2.25" x 3.5" MicroPython & FreeRTOS iotdesign.embedded-computing.com/p374585

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info@emacinc.com  618-529-4525 www.linkedin.com/company/emac-inc-/

 @emac_inc

www.embedded-computing.com/iot

FWM8BLZ-Series Standard and Sensor Beacons Fujitsu offers a family of Bluetooth v4.1 standard and sensor-embedded beacons. Ranging from broadcast-only units to those with accelerometer and temperature sensors and data log function, these beacons address a range of indoor navigation, retail marketing, asset management, healthcare, Point-of-Presence, and IoT platform applications. They are based on Fujitsu Bluetooth® Low Energy (BLE) Modules, which contain the complete verified and qualified Bluetooth low energy protocol stack, to offer flexibility and a high level of customization.

The beacons feature selectable operating modes and can be reconfigured via Over-the-Air updating. They have an operating temperature range of -30 to +60 °C, and a 2 year operating life using a CR2450 coin cell battery and a 1 second advertise interval. Measuring a compact 40 x 31 x 12mm, several are iBeacon™ and Eddystone™ compliant and compatible with enmo IoT.Over.Beacon technology. Sample codes for iOS and Android™ are available from Fujitsu to assist with developing smartphone application software.

FEATURES ĄĄ Bluetooth specification version 4.1(single mode) ĄĄ OTA configuration mode ĄĄ LED status ĄĄ Long operation life with coin cell battery ĄĄ Pattern antenna ĄĄ Transmit power: -16, -12, -8, -4, 0, +4dBm ĄĄ Certifications: QDID, FCC, IC, CE, Radio Act iotdesign.embedded-computing.com/p374581

Fujitsu Components America

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components@us.fujitsu.com

 800-380-0059

 www.linkedin.com/company/fujitsu-components/

www.fujitsu.com/us/products/devices/components/wireless-modules/beacons/

Wireless

REAL TIME MICRO LOCATION REFERENCE SOLUTION (Based on ultra wide-band technology)

R T L S

Developing micro location applications that can track assets/ people in real time? PathPartner’s RTLS Reference Solution provides complete foundation hardware, embedded software and cloud software coupled with product engineering services to accelerate your next micro-location solution development.

Some of the key highlights include: • Enables in-campus indoor and outdoor positioning, with ultra high precision • Based on ultra wideband (uses underlying IEEE 802.15.4-2011) technology • Complete hardware and software building blocks – customizable for your requirements • Suitable for tracking, navigation, geo-fencing, and location aware use-cases • Applications: Asset management, factory automation, warehousing, logistics, multi-level parking, healthcare, retail and more

PathPartner Technology

www.pathpartnertech.com www.embedded-computing.com/iot

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FEATURES High precision: Provides location accuracy of up to 10cms Highly reliable: Lower interference (since it uses frequencies outside the crowded 2.4GHz band) ĄĄ Low power: Uses ultra-low power chipsets from leading semiconductor majors ĄĄ Expandable: Customizable peripherals such as motion detection sensors, NFC, GPS, altimeter for your target application ĄĄ ĄĄ

iotdesign.embedded-computing.com/p374583

marcom@pathpartnertech.com www.linkedin.com/company/pathpartnertechnology/

 +1 408 242 7411 @pathpartner

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Balance is Ever ything

We make superior solid state storage and memory for industrial IoT ecosystems, with the optimum balance of quality, data integrity and cost-efficiency.

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Twenty years refined U.S. production and 100% testing - unlike offshore competition

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A+ quality: 98.8% yield, 99.7% on-time delivery and 86 field-defects-per-million*

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Extreme durability, longer life-cycles and intelligent, secure edge solutions

Visit our website to learn more and let’s keep the balance - together.

Familiar Done Differently ®

Solid State Storage and Memory

*QA marks averaged through entire year of 2017.

Copyright 2018, Virtium LLC. Top image copyright: 123RF/Orla

www.virtium.com