Category Archives: Design Trends

Security coprocessor marks a new approach to provisioning for IoT edge devices


It’s worth noting that security breaches rarely involve breaking the encryption code; hackers mostly use techniques like spoofing to steal the ID.


The advent of security coprocessor that offloads the provisioning task from the main MCU or MPU is bringing new possibilities for the Internet of Things product developers to secure the edge device at lower cost and power points regardless of the scale.

Hardware engineers often like to say that there is now such thing as software security, and quote Apple that has all the money in the world and an army of software developers. The maker of the iPhone chose a secure element (SE)-based hardware solution while cobbling the Apple Pay mobile commerce service. Apparently, with a hardware solution, engineers have the ecosystem fully in control.

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Security is the basic building block of the IoT bandwagon, and there is a lot of talk about securing the access points. So far, the security stack has largely been integrated into the MCUs and MPUs serving the IoT products. However, tasks like encryption and authentication take a lot of battery power — a precious commodity in the IoT world.

Atmel’s solution: a coprocessor that offloads security tasks from main MCU or MPU. The ATECC508A uses elliptic curve cryptography (ECC) capabilities to create secure hardware-based key storage for IoT markets such as home automation, industrial networking and medical. This CryptoAuthentication chip comes at a manageable cost — 50 cents for low volumes — and consumers very low power. Plus, it makes provisioning — the process of generating a security key — a viable option for small and mid-sized IoT product developers.

A New Approach to Provisioning

It’s worth noting that security breaches rarely involve breaking the encryption code; hackers mostly use techniques like spoofing to steal the ID. So, the focus of the ATECC508A crypto engine is the tasks such as key generation and authentication. The chip employs ECC math to ensure sign-verify authentication and subsequently the verification of the key agreement.

The IoT security — which includes the exchange of certificates and other trusted objects — is implemented at the edge node in two steps: provisioning and commissioning. Provisioning is the process of loading a unique private key and other certificates to provide identity to a device while commissioning allows the pre-provisioned device to join a network. Moreover, provisioning is carried out during the manufacturing or testing of a device and commissioning is performed later by the network service provider and end-user.

Atmel ATECC508A crypto-engine

Presently, snooping threats are mostly countered through hardware security module (HSM), a mechanism to store, protect and manage keys, which requires a centralized database approach and entails significant upfront costs in infrastructure and logistics. On the other hand, the ATECC508A security coprocessor simplifies the deployment of secure IoT nodes through pre-provisioning with internally generated unique keys, associated certificates and certification-ready authentication.

It’s a new approach toward provisioning that not only prevents over-building, as done by the HSM-centric techniques, but also prevents cloning for the gray market. The key is controlled by a separate chip, like the ATECC508A coprocessor. Meaning, if there are 1,000 IoT systems to be built, there will be exactly 1,000 security coprocessors for them.

Certified-ID Security Platform

Back at ARM TechCon 2015, Atmel went one step ahead when it announced the availability of Certified-ID security platform for the IoT entry points like edge devices to acquire certified and trusted identities. This platform leverages internal key generation capabilities of the ATECC508A security coprocessor to deliver distributed key provisioning for any device joining the IoT network. That way it enables a decentralized secure key generation and eliminates the upfront cost of building the provisioning infrastructure for IoT setups being deployed at smaller scales.

AT88CKECCROOT-SIGNER

Atmel, a pioneer in Trusted Platform Module (TPM)-based secure microcontrollers, is now working with cloud service providers like Proximetry and Exosite to turn its ATECC508A coprocessor-based Certified-ID platform into an IoT edge node-to-cloud turnkey security solution. TPM chips, which have roots in the computer industry, aren’t well-positioned to meet the cost demands of low-price IoT edge devices.

Additionally, the company has announced the availability of two provisioning toolkits for low volume IoT systems. The AT88CKECCROOT toolkit is a ‘master template’ that creates and manages certificate root of trust in any IoT ecosystem. On the other hand, AT88CKECCSIGNER is a production kit that allows designers and manufacturers to generate tamper-resistant keys and security certifications in their IoT applications.

mbed eval boards showcase focus on IoT software and connectivity


Chipmakers like Atmel are joining hands with ARM to bring the entire ecosystem under one roof and thus facilitate the creation of standards-based IoT products.


ARM’s mbed operating system is winning attention in the highly fragmented embedded software space by promising a solid software foundation for interoperable hardware and thus scale the Internet of Things designs by narrowing the development time.

Atmel has put its weight behind ARM’s mbed OS by launching the single-chip evaluation board for the IoT ecosystem in a bid to ensure low software dependence for the embedded developers. The leading microcontroller supplier unveiled the mbed evaluation platform at the recent ARM TechCon held in Santa Clara, California.

The mbed OS platform is focused on rapid development of connected devices with an aim to create a serious professional platform to prototype IoT applications. So IoT developers don’t have to look to software guys for help. The mbed stack features a strong focus on enhancing the IoT’s connectivity and software components.

Atmel mbed Xpro board

ARM is the lead maintainer for the mbed OS modules while it adds silicon partners, like Atmel, as platform-specific dependencies for the relevant mbed OS modules. Silicon partners are responsible for their platform-specific drivers.

Atmel’s mbed-enabled evaluation board is based on the low-power 2.4GHz wireless Cortex-M0+ SAM R21 MCU. Moreover, Atmel is expanding mbed OS support for its Wi-Fi modules and Bluetooth Low Energy products.

The fact that Atmel is adding mbed OS to its IoT ecosystem is an important nod for ARM’s mbed technology in its journey from merely a hardware abstraction layer to a full-fledged IoT platform. Atmel managers acknowledge that mbed technology adds diversity to embedded hardware devices and makes MCUs more capable.

Solid Software Foundation

There is a lot of code involved in the IoT applications and software is getting more complex. It encompasses, for instance, sensor library to acquire data, authentication at IoT gateways and SSL security. Here, the automatic software integration engine like mbed lets developers focus on their applications instead of worrying about integrating off-the-shelf software.

The mbed reference designs like the one showcased by Atmel during ARM TechCon are aimed at narrowing the development time with the availability of building blocks and design resources—components, code and infrastructure—needed to bootstrap a working IoT system. Atmel managers are confident that a quality software foundation like mbed could help bring IoT products to market faster.

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Atmel’s mbed-enabled IoT evaluation board promises harmony between hardware and software. Apparently, chipmakers like Atmel are joining hands with ARM to bring the entire ecosystem — OS software, cloud services and developer tools — under one roof, and thus facilitate the creation of standards-based IoT products. Atmel’s mbed evaluation board clearly mirrors that effort to deliver a complete hardware, software and developer tools ecosystem in order to bring IoT designs quicker to market.

The platform comprises of mbed OS software for IoT client devices like gateways and mbed Device Server for the cloud services. ARM launched the mbed software platform in 2014 and Atmel has been part of this initiative since then.

mbed in Communications Stack

Additionally, Atmel has tied the mbed association to its SmartConnect wireless solutions to make the best of mbed’s networking stack in the Internet of connected things. The IoT technology is built on layers, and here, interoperability of communications protocols is a key challenge.

For a start, Atmel’s SAM R21-Xpro evaluation board is embed-enabled and is built around the R21 microcontroller, which has been designed for industrial and consumer wireless applications running proprietary communication stacks or IEEE 802.15.4-compliant solutions.

Next up, the evaluation board includes SAM W25 Wi-Fi module that integrates IEEE 802.11 b/g/n IoT network controller with the existing MCU solution, SAM D21, which is also based on the Cortex-M0+ processor core.

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Furthermore, Atmel is offering an mbed-enabled Bluetooth starter kit that includes SAM L21 microcontroller-based evaluation board and ultra-low-power Bluetooth chip BTLC1000, which is compliant with Bluetooth Low Energy 4.1. Atmel demonstrated a home lighting system at the ARM TechCon show floor, which employed SAM R21-based Thread routers that passed light sensor information to an mbed-enabled home gateway. Subsequently, this information was processed and sent to the mbed Device Server using a web interface.


Majeed Ahmad is the author of books Smartphone: Mobile Revolution at the Crossroads of Communications, Computing and Consumer Electronics and The Next Web of 50 Billion Devices: Mobile Internet’s Past, Present and Future.

Who’s winning the Arduino popularity contest?


You think Arduino is popular? Wait until you see some of the numbers our friends at codebender have compiled.


If you’ve ever wondered which Arduino boards are the most popular, which are the most used processors, which are the most common Libraries (and Example) and how are they being used, you’ll appreciate this post from codebender founder Vasilis Georgitzikis. For those of you who may not be familiar with the site, codebender is an online Arduino IDE that enables you to program your ‘duino on the cloud.

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“At codebender we have a unique insight on this, since we have more than 40,000 people using codebender to write Arduino code, and more than 100,000 sketches. This gives us the ability to gather anonymous data on board usage, popular boards, etc. And since we host more than 500 built-in libraries, we also get a great view on the preferred Libraries as well,” Georgitzikis explains.

The Most Popular Kid on the Block

First, codebender took a look into the popularity of each Arduino board. The easiest way to count this is to take a look at which board people use most often. They counted how many times people programmed/”flashed” a particular board (say, an Arduino Uno) versus the total number of times someone programmed a board on codebender during September (which was 123,967 times).

Before diving into the data, a few things should first be noted:

  • When you look at this, keep in mind that codebender only supports AVR-based boards right now, so boards like the Due, Zero and Galileo/Edison are not counted here.
  • This research is based on usage on codebender, not across all Arduino users. But there’s no reason to think that this would be any different, so it’s fair to say that what is seen here applies to the Arduino community at large.
  • There is a caveat to the above — codebender has some partnerships with hardware manufacturers who suggest codebender for their boards, so naturally there will be slightly inflated numbers for these.

So, without further ado, here are the results (showing only boards with more than 1% usage):

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Wow! Everyone knows Arduino Uno is the most popular board, but did you know that in more than half of the instances an Arduino is programmed, it’s an Arduino Uno?

“I also personally didn’t expect the Arduino Nano to be so popular, let alone #2! I’m more of a Pro Mini/Pro Micro guy myself, since I’m a bit of a SparkFun nerd. A reason for this spike could be the recent surge of ridiculously affordable Arduino Nano-compatible boards from China, using the very inexpensive CH340G chip for the USB-to-Serial instead of the more common FTDI chip,” Georgitzikis adds.

Another thing worth mentioning is the number of Duemilanove boards still in existence (remember, they are six years old), which are still almost as popular as the Leonardo.

“The Leonardo, by the way, is much lower than I expected. It goes to show that issues with the way the Leonardo’s programming was implemented – the less-than-stellar robustness when programming and all the inconsistencies it brings with existing code and Libraries – outweigh the extra features and lower price,” Georgitzikis shares. “Long live the Uno!”

(By the way, notice that 4 out of the 13 most popular boards are manufactured by SparkFun. Not bad, huh?)

Official Boards Only

Okay, as mentioned above, some boards are bound to be a bit inflated because their manufacturer suggests codebender as the tool of choice for Arduino coding. Let’s look at the same numbers, this time using only the official Arduino boards.

According to codebender, here are the results (showing only boards with more than 1% usage):

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Old But Gold

For its last chart, the codebender crew thought it would be interesting to see the most popular microprocessor chip in Arduino land.

On the left chart, they measured the number of boards that use a certain chip. Out of the 80 boards that codebender supports, how many boards use each chip? The right chart reveals the number of times an Arduino is programmed, so you can see how many times people programed a board with a certain processor (i.e. ATmega328), compared to the total number of times people programmed a board.

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And the winner is, of course, the ATmega328 by a landslide.

“First, we see that a good third of the boards supported in codebender are using the ATmega328. ATtiny in second place seems weird at first, but given that there are around 20 different boards for the various ATtiny chips and configurations, it makes sense,” Georgitzikis writes. “And then, you have the ATmega32U4 devices. There are a lot of independent manufacturers making boards based on this chip, but as we saw on the previous chart (and as you can see on the Processor Usage chart above), they end up not being used too frequently.”

As you can see on the Processor Usage chart, more than four out of five times someone programs an Arduino, it’s using an ATmega328. Isn’t that simply amazing? (We sure think so!)

Editor’s note: These insights are based on anonymous usage data gathered by codebender. 

[h/t SparkFun]

Are you designing for the latest automotive embedded system?


Eventually, self-driving cars will arrive. But until then, here’s a look at what will drive that progression.


The next arrow of development is set for automotive

We all have seen it. We all have read about it in your front-center technology news outlets. The next forefront for technology will take place in the vehicle. The growing market fitted with the feature deviation trend does not appeal to the vision of customizing more traditional un-connected, oiled and commonly leveraged chassis vehicles of today. Instead, ubiquity in smartphones have curved a design trend, now mature while making way for the connected car platform. The awaiting junction is here for more integration of the automotive software stack.  Opportunities for the connected car market are huge, but multiple challenges still exist. Life-cycles in the development of automotive and the mobile industry are a serious barrier for the future of connected cars. Simply, vehicles take much longer to develop than smartphones other portable gadgetry. More integration from vendors and suppliers are involved with the expertise to seamlessly fit the intended blueprint of the design. In fact, new features such as the operating system are becoming more prevalent, while the demand for sophisticated and centrally operated embedded systems are taking the height of the evolution. This means more dependence on integration of data from various channels, actuators, and sensors — the faculty to operate all the new uses cases such as automatic emergency response systems are functionality requiring more SoC embedded system requirements.

A step toward the connected car - ecall and how it works

What is happening now?

People. Process. Governance. Adoption. Let’s look at the similarities stemmed from change. We are going to witness new safety laws and revised regulations coming through the industry. These new laws will dictate the demand for connectivity. Indeed, drawing importance this 2015 year with the requirement set by 2018, European Parliament voted in favor of eCall regulation. Cars in Europe must be equipped with eCall, a system that automatically contacts emergency services directing them to the vehicle location in the event of an emergency. The automotive and mobile industries have different regional and market objectives. Together, all the participants in both market segments will need to find ways to collaborate in order to satisfy consumer connectivity needs. Case in point, Chrysler has partnered with Nextel to successfully connect cars like their Dodge Viper, while General Motors uses AT&T as its mobile development partner.

General Motors selected AT&T as its mobile partner

What is resonating from the sales floor and customer perspective?

The demand is increasing for more sophistication and integration of software in the cabin of cars. This is happening from the manufacturer to the supplier network then to the integration partners — all are becoming more engaged to achieve the single outcome, pacing toward the movement to the connected car. Stretched as far as the actual retail outlets, auto dealers are shifting their practice to be more tech savvy, too. The advent of the smart  vehicle has already dramatically changed the dealership model, while more transformation awaits the consumer.

On the sales floor as well as the on-boarding experience, sales reps must plan to spend an hour or more teaching customers how to use their car’s advanced technology. But still, these are only a few mentioned scenarios where things have changed in relation to cars and how they are sold and even to the point of how they are distributed, owned, and serviced. One thing for certain, though, is that the design and user trend are intersecting to help shape the demand and experience a driver wants in the connected car. This is further bolstered by the fast paced evolution of smartphones and the marketing experiences now brought forth by the rapid adoption and prolific expansion of the mobile industry tethered by their very seamless and highly evolved experiences drawn from their preferred apps.

Today, customer experiences are becoming more tailored while users, albeit on the screen or engaged with their mobile devices are getting highly acquainted with the expectation of “picking up from where I left off” regardless of what channel, medium, device, or platform.  Seamless experiences are breaking through the market.  We witness Uber, where users initialize their click on their smartphone then follows by telemetry promoted from Uber drivers and back to the users smart phone.  In fact, this happens vis versa, Uber driver’s have information on their console showing customer location and order of priority.  Real life interactions are being further enhanced by real-time data, connecting one device to draw forth another platform to continue the journey.  Transportation is one of the areas where we can see real-time solutions changing our day-to-day engagement.  Some of these are being brought forth by Atmel’s IoT cloud partners such as PubNub where they leverage their stack in devices to offer dispatch, vehicle state, and geo fencing for many vehicle platforms.  Companies like Lixar, LoadSmart, GetTaxi, Sidecar, Uber, Lyft are using real-time technologies as integral workings to their integrated vehicle platforms.

The design trajectory for connected cars continues to follow this arrow forward

Cars are becoming more of a software platform where value chain add-ons tied to an ecosystem are enabled within the software tethered by the cloud where data will continue to enhance the experience. The design trajectory for connected cars follow this software integration arrow.  Today, the demand emphasizes mobility along with required connectivity to customer services and advanced functions like power management for electric vehicles, where firmware/software updates further produce refined outcomes in the driver experience (range of car, battery management, other driver assisted functionalities).

Carmakers and mobile operators are debating the best way to connect the car to the web. Built-in options could provide stronger connections, but some consumers prefer tethering their existing smartphone to the car via Bluetooth or USB cable so they can have full access to their personal contacts and playlists. Connected car services will eventually make its way to the broader car market where embedded connections and embedded systems supporting these connections will begin to leverage various needs to integrate traditional desperate signals into a more centrally managed console.

Proliferation of the stack

The arrow of design for connected cars will demand more development, bolstering the concept that software and embedded systems factored with newly-introduced actuators and sensors will become more prevalent. We’re talking about “software on wheels,” “SoC on wheels,” and “secured mobility.”

Design wise, the cost-effective trend will still remain with performance embedded systems. Many new cars may have extremely broad range of sensor and actuator‑based IoT designs which can be implemented on a single compact certified wireless module.

The arrow for connected cars will demand more development bolstering the concept that software and embedded systems factored with newly introduced actuators & sensors will become more prevalent; “software on wheels”, “SoC on wheels” and “secured mobility”.

Similarly, having fastest startup times by performing the task with a high-performance MCU vs MPU, is economic for a designer. It can not only reduce significant bill of materials cost, development resources, sculpted form factor, custom wireless design capabilities, but also minimize the board footprint. Aside from that, ARM has various IoT device development options, offering partner ecosystems with modules that have open standards. This ensures ease of IoT or connected car connectivity by having type approval certification through restrictive access to the communications stacks.

Drivers will be prompted with new end user applications — demand more deterministic code and processing with chips that support the secure memory capacity to build and house the software stack in these connected car applications.

Feature upon feature, layer upon layer of software combined with characteristics drawn from the events committed by drivers, tires, wheels, steering, location, telemetry, etc. Adapted speed and braking technologies are emerging now into various connected car makes, taking the traditional ABS concept to even higher levels combined with intelligence, along with controlled steering and better GPS systems, which will soon enable interim or cruise hands-free driving and parking.

Connected Car Evolution

Longer term, the technological advances behind the connected car will eventually lead to self-driving vehicles, but that very disruptive concept is still far out.

Where lies innovation and change is disruption

Like every eventual market disruption, there will be the in-between development of this connected car evolution. Innovative apps are everywhere, especially the paradigm where consumers have adopted to the seamless transitional experiences offered by apps and smartphones. Our need for ubiquitous connectivity and mobility, no matter where we are physically, is changing our vehicles into mobile platforms that want us users to seamlessly be connected to the world. This said demand for connectivity increases with the cost and devices involved will become more available. Cars as well as other mobility platforms are increasingly becoming connected packages with intelligent embedded systems. Cars are offering more than just entertainment — beyond providing richer multimedia features and in-car Internet access.  Further integration of secure and trusted vital data and connectivity points (hardware security/processing, crypto memory, and crypto authentication) can enable innovative navigation, safety and predictive maintenance capabilities.

Carmakers are worried about recent hacks,  especially with issues of security and reliability, making it unlikely that they will be open to every kind of app.  They’ll want to maintain some manufactured control framework and secure intrusion thwarting with developers, while also limiting the number of apps available in the car managing what goes or conflicts with the experience and safety measures.  Importantly, we are taking notice even now. Disruption comes fast, and Apple and others have been mentioned to enter this connected car market. This is the new frontier for technological equity scaling and technology brand appeal. Much like what we seen in the earlier models of Blackberry to smartphones, those late in the developmental evolution of their platforms may be forced adrift or implode by the market.

No one is arguing it will happen. Eventually, self-driving cars will arrive.  But for now, it remains a futuristic concept.

What can we do now in the invention, design and development process?

The broader output of manufactured cars will need to continue in leveraging new designs that take in more integration of traditional siloed integration vendors so that the emergence of more unified and centrally managed embedded controls can make its way. Hence, the importance now exists in the DNA of a holistically designed platform fitted with portfolio of processors and security to take on new service models and applications.

This year, we have compiled an interesting mixture of technical articles to support the development and engineering of car access systems, CAN and LIN networks, Ethernet in the car, capacitive interfaces and capacitive proximity measurement.

In parallel to the support of helping map toward the progress and evolution of the connected car, a new era of design exists. One in which the  platform demands embedded controls to evenly match their design characteristics and application use cases. We want to also highlight the highest performing ARM Cortex-M7 based MCU in the market, combining exceptional memory and connectivity options for leading design flexibility. The Atmel | SMART ARM Cortex-M7 family is ideal for automotive, IoT and industrial connectivity markets. These SAM V/E/S family of microcontrollers are the industry’s highest performing Cortex-M microcontrollers enhancing performance, while keeping cost and power consumption in check.

So are you designing for the latest automotive, IoT, or industrial product? Here’s a few things to keep in mind:

  • Optimized for real-time deterministic code execution and low latency peripheral data access
  • Six-stage dual-issue pipeline delivering 1500 CoreMarks at 300MHz
  • Automotive-qualified ARM Cortex-M7 MCUs with Audio Video Bridging (AVB) over Ethernet and Media LB peripheral support (only device in the market today)
  • M7 provides 32-bit floating point DSP capability as well as faster execution times with greater clock speed, floating point and twice the DSP power of the M4

We are taking the connected car design to the next performance level — having high-speed connectivity, high-density on-chip memory, and a solid ecosystem of design engineering tools. Recently, Atmel’s Timothy Grai added a unveiling point to the DSP story in Cortex-M7 processor fabric. True DSPs don’t do control and logical functions well; they generally lack the breadth of peripherals available on MCUs. “The attraction of the M7 is that it does both — DSP functions and control functions — hence it can be classified as a digital signal controller (DSC).” Grai quoted the example of Atmel’s SAM V70 and SAM V71 microcontrollers are used to connect end-nodes like infotainment audio amplifiers to the emerging Ethernet AVB network. In an audio amplifier, you receive a specific audio format that has to be converted, filtered, and modulated to match the requirement for each specific speaker in the car. Ethernet and DSP capabilities are required at the same time.

“The the audio amplifier in infotainment applications is a good example of DSC; a mix of MCU capabilities and peripherals plus DSP capability for audio processing. Most of the time, the main processor does not integrate Ethernet AVB, as the infotainment connectivity is based on Ethernet standard,” Grai said. “Large SoCs, which usually don’t have Ethernet interface, have slow start-up time and high power requirements. Atmel’s SAM V7x MCUs allow fast network start-up and facilitate power moding.”

Atmel has innovative memory technology in its DNA — critical to help fuel connected car and IoT product designers. It allows them to run the multiple communication stacks for applications using the same MCU without adding external memory. Avoiding external memories reduces the PCB footprint, lowers the BOM cost and eliminates the complexity of high-speed PCB design when pushing the performance to a maximum.

Importantly, the Atmel | SMART ARM Cortex-M7 family achieves a 1500 CoreMark Score, delivering superior connectivity options and unique memory architecture that can accommodate the said evolve of the eventual “SoC on wheels” design path for the connected car.

How to get started

  1. Download this white paper detailing how to run more complex algorithms at higher speeds.
  2. Check out the Atmel Automotive Compilation.
  3. Attend hands-on training onboard the Atmel Tech on Tour trailer. Following these sessions, you will walk away with the Atmel | SMART SAM V71 Xplained Ultra Evaluation Kit.
  4. Design the newest wave of embedded systems using SAM E70, SAM S70, or SAM V70 (ideal for automotive, IoT, smart gateways, industrial automation and drone applications, while the auto-grade SAM V70 and SAM V71 are ideal for telematics, audio amplifiers and advanced media connectivity).

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[Images: European Commission, GSMA]

Profile of an IoT processor for the industrial and consumer markets


 If there’s a single major stumbling block that is hindering the IoT take-off at the larger industrial scale, it’s security.


The intersection of data with intelligent machines is creating new possibilities in industrial automation, and this new frontier is now being increasingly known as the Industrial Internet of Things (IIoT). However, if there is a single major stumbling block that is hindering the IoT take-off at the larger industrial scale, it’s security.

It’s imperative to have reliable data in the industrial automation environment, and here, the additional security layers in the IoT hardware often lead to compromises in performance. Then, there is counterfeiting of products and application software, which is becoming a growing concern in the rapidly expanding IoT market.

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Atmel’s answer to security concerns in the IIoT infrastructure: a microprocessor (MPU) that can deliver the security while maintaining the level of performance that Internet-connected systems require. The company’s Cortex A5 chip — the Atmel | SMART SAMA5D4 — securely stores and transfers data, as well as safeguards software assets to prevent cloning of IoT applications.

The SAMA5D4 series of MPUs enables on-the-fly encryption and decryption of software code from the external DRAM. Moreover, it boasts security features such as secure boot, tamper detection pins and safe erasure of security-critical data. The A5D4 processor also incorporates ARM’s system-wide security approach, TrustZone, which is used to secure peripherals such as memory and crypto blocks. TrustZone —comprising of security extensions that can be implemented in a number of ARM cores — is tightly integrated into ARM’s Cortex-A processors. It runs the processor in two different modes: First, a secure environment executes critical security and safety software, and secondly, a normal environment runs the rich OS software applications such as Linux. This lets embedded designers isolate critical software from OS software.

The system approach allows control access to CPU, memories, DMA and peripherals with programmable secure regions. That, in turn, ensures that on-chip parts like CPU and off-chip parts like peripherals are protected from software attacks.

Trust

Performance Uplift

The Atmel SMART | SAMA5D4 processor is based on the Cortex-A5, the smallest and simplest of the Cortex-A series cores that support the 32-bit ARMv7 instruction set. It’s targeted at applications requiring high-precision computing and fast signal processing — that includes industrial and consumer applications such as control panels, communication gateways and imaging terminals.

The use cases for SAMA5D4 span from kiosks, vending machines and barcode scanners, to smart grid, communications gateways and control panels for security, home automation, thermostats, etc. Atmel’s MPU features peripherals for connectivity and user interface applications. For instance, it offers a TFT LCD controller for human-machine interface (HMI) and control panel applications and a dual Ethernet MAC for networking and gateway solutions.

Apart from providing high-grade security, SAMA5D4 adds two other crucial features to address the limitations of its predecessor, SAMA5D3 processor. First, it uplifts performance through ARM’s NEON DSP engine and 128kB L2 cache. The NEON DSP with 128-bit single instruction, multiple data (SIMD) architecture accelerates signal processing for more effective handling of multimedia and graphics. Likewise, L2 cache enhances data processing capability for imaging applications.

The second prominent feature of the SAMA5D4 is video playback that boasts 720p resolution hardware video decoder with post-image processing capability. Atmel’s embedded processor offers video playback for H.264, VP8 and MPEG4 formats at 30fps.

A Quick Overview of the SAMA5D4

The SAMA5D4 processor, which got a 14 percent performance boost from its predecessor MPU, increasing operating speed to 528 MHz, is a testament of the changing microprocessor market in the IoT arena. Atmel’s microprocessor for IoT markets delivers 840 DMIPS that can facilitate imaging-centric applications hungry for processing power. Aside from that, the SAMA5D4 is equipped with a 32-bit wide DDR controller running up to 176 MHz, which can deliver up to 1408MB/s of bandwidth. That’s a critical element for high-speed peripherals common in the industrial environments where microprocessors are required to process large amounts of data.

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Finally, the SAMA5D4 is configurable in either a 16- or 32-bit bus interface allowing developers a trade-off between performance and memory cost. There are four distinct chips in the SAMA5D4 family: SAMA5D41 (16-bit DDR), SAMA5D42 (32-bit DDR), SAMA5D43 (16-bit DDR along with H.264 video decoder)and SAMA5D44 (32-bit DDR along with H.264 video decoder).

The SoC-specific hardware security and embedded vision capabilities are a stark reminder of specific requirements of different facets of IoT, in this case, industrial and consumers markets. And Atmel’s specific focus on security and rich media just shows how the semiconductor industry is getting around the key IoT stumbling blocks.


Majeed Ahmad is the author of books Smartphone: Mobile Revolution at the Crossroads of Communications, Computing and Consumer Electronics and The Next Web of 50 Billion Devices: Mobile Internet’s Past, Present and Future.

How Ethernet AVB is playing a central role in automotive streaming applications


Ethernet is emerging as the network of choice for infotainment and advanced driver assistance systems, Atmel’s Tim Grai explains.


Imagine you’re driving down the highway with the music blaring, enjoying the open road. Now imagine that the sound from your rear speaker system is delayed by a split second from the front; your enjoyment of the fancy in-car infotainment system comes to a screeching halt.

Ethernet is emerging as the network of choice for infotainment and advanced driver assistance systems that include cameras, telematics, rear-seat entertainment systems and mobile phones. But standard Ethernet protocols can’t assure timely and continuous audio/video (A/V) content delivery for bandwidth intensive and latency sensitive applications without buffering, jitter, lags or other performance hits.

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Audio-Video Bridging (AVB) over Ethernet is a collection of extensions to the IEEE802.1 specifications that enables local Ethernet networks to stream time synchronised, loss sensitive A/V data. Within an Ethernet network, the AVB extensions help differentiate AVB traffic from the non-AVB traffic that can also flow through the network. This is done using an industry standard approach that allows for plug-and-play communication between systems from multiple vendors.

The extensions that define the AVB standard achieve this by:

  • reserving bandwidth for AVB data transfers to avoid packet loss due to network congestion from ‘talker’ to ‘listener(s)’
  • establishing queuing and forwarding rules for AVB packets that keep packets from bunching and guarantee delivery of packets with a bounded latency from talker to listener(s) via intermediate switches, if needed
  • synchronizing time to a global clock so the time bases of all network nodes are aligned precisely to a common network master clock, and
  • creating time aware packets which include a ‘presentation time’ that specifies when A/V data inside a packet has to be played.

Designers of automotive A/V systems need to understand the AVB extensions and requirements, as well as how their chosen microcontroller will support that functionality.

AVB: A basket of standards

AVB requires that three extensions be met in order to comply with IEEE802.1:

  • IEEE802.1AS – timing and synchronisation for time-sensitive applications (gPTP)
  • IEEE802.1Qat – stream reservation protocol (SRP)
  • IEEE802.1Qav – forwarding and queuing for time-sensitive streams (FQTSS).

In order to play music or video from one source, such as a car’s head unit, to multiple destinations, like backseat monitors, amplifiers and speakers, the system needs a common understanding of time in order to avoid lags or mismatch in sound or video. IEEE802.1AS-2011 specifies how to establish and maintain a single time reference – a synchronised ‘wall clock’ – for all nodes in a local network. The generalized precision time protocol (gPTP), based on IEEE1588, is used to synchronize and syntonize all network nodes to sub-microsecond accuracy. Nodes are synchronized if their clocks show the same time and are syntonised if their clocks increase at the same rate.

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This protocol selects a Grand Master Clock from which the current time is propagated to all network end-stations. In addition, the protocol specifies how to correct for clock offset and clock drifts by measuring path delays and frequency offsets. New MCUs, such as the Atmel | SMART SAMV7x (shown above), detect and capture time stamps automatically when gPTP event messages cross MII layers. They can also transport gPTP messages over raw Ethernet, IPv4 or IPv6. This hardware recognition feature helps to calculate clock offset and link delay with greater accuracy and minimal software load.

Meanwhile, SRP guarantees end-to-end bandwidth reservation for all streams to ensure packets aren’t delayed or dropped at any switch due to network congestion, which can occur with standard Ethernet. For the in-vehicle environment, SRP is typically configured in advance by the car maker, who defines data streams and bandwidth allocations.

Talkers (the source of A/V data) ‘advertise’ data streams and their characteristics. Switches process these announcements from talker and listeners to:

  • register and prune streams’ path through the network
  • reserve bandwidth and prevent over subscription of available bandwidth
  • establish forwarding rules for incoming packets
  • establish the SRP domain, and
  • merge multiple listener declarations for the same stream

The standard stipulates that AVB data can reserve only 75% of total available bandwidth, so for a 100Mbit/s link, the maximum AVB data is 75Mbit/s. The remaining bandwidth can be used for all other Ethernet protocols.

In automotive systems, the streams may be preconfigured and bandwidth can be reserved statically at system startup to reduce the time needed to bring the network into a fully operational state. This supports safety functions, such as driver alerts and the reversing camera, that must be displayed within seconds.

SRP uses other signalling protocols, such as Multiple MAC Registration Protocol, Multiple VLAN Registration Protocol and Multiple Stream Registration Protocol to establish bandwidth reservations for A/V streams dynamically.

The third extension is FQTSS, which guarantees that time sensitive A/V streams arrive at their listeners within a bounded latency. It also defines procedures for priority regenerations and credit based traffic shaper algorithms to meet stream reservations for all available devices.

The AVB standard can support up to eight traffic classes, which are used to determine quality of service. Typically, nodes support at least two traffic classes – Class A, the highest priority, and Class B. Microcontroller features help manage receive and transmit data with multiple priority queues to support AVB and ‘best effort class’ non AVB data.

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Automotive tailored requirements

Automotive use cases typically fix many parameters at the system definition phase, which means that AVB implementation can be optimised and simplified to some extent.

  • Best Master Clock algorithm (BMCA): the best clock master is fixed at the network definition phase so dynamic selection using BCMA isn’t needed.
  • SRP: all streams, their contents and their characteristics are known at system definition and no new streams are dynamically created or destroyed; the proper reservation of data is known at the system definition phase; switches, talkers and listeners can have their configurations loaded at system startup from pre-configured tables, rather than from dynamic negotiations
  • Latency; while this is not critical, delivery is. Automotive networks are very small with only a few nodes between a talker and listener. It is more important not to drop packets due to congestion.

Conclusion

The requirement to transfer high volumes of time sensitive audio and video content inside vehicles necessitates developers to understand and apply the Ethernet AVB extensions. AVB standardization results in interoperable end-devices from multiple vendors that can deliver audio and video streams to distributed equipment on the network with micro-second accuracy or better. While the standard brings complexities, new MCUs with advanced features are simplifying automotive A/V design.


This article was originally published on New Electronics on October 13, 2015 and authored by Tim Grai, Atmel’s Director of Automotive MCU Application Engineering. 

SOMNIUM’s DRT software tools now available in Atmel Studio 7


Build smaller, faster, cheaper and more energy efficient software for Atmel | SMART devices with the SOMNIUM DRT Atmel Studio Extension.


As the desire for the world to become more connected increases by the day, we see more and more devices connecting to each other and sensors being built into everything around us. The advent of the Internet of Things means that MCUs need to be smaller and more energy efficient than ever before, but at the same time these processors need to be smarter and cheaper, and from a developers perspective, need to be easy to program as well.

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Fortunately, the Atmel | SMART ARM-based family has been optimized for cost and power sensitive use cases, targeting applications such as the IoT, smart metering, industrial controls and domestic appliances, to name just a few. Moreover, the recently launched Atmel Studio 7 has introduced a new capability to measure energy consumption during development — a clear indication of the growing significance of this factor to developers in their embedded designs.

Easily measuring energy consumption during development is clearly important, but once you know your consumption what steps can you take if you need to reduce usage in your design? The MCU itself certainly contributes, and typically a smaller device will need lower power. As a result, many designers’ first strategy is keep the energy consumption low in their design is to reduce code size, thus allowing them to devise on a smaller MCU. This often requires a fair amount of manual code optimization, a time consuming and costly task.

What if there was a way for you to not only take advantage of the innovative Atmel | SMART MCU lineup and the added features of Atmel Studio 7, but also take your embedded software designs to the next level, further reducing your energy consumption, shrinking your code size without manual intervention and at the same time improving performance? Now there is, thanks to the SOMNIUM DRT Atmel Studio Extension.

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DRT supports all Atmel | SMART ARM Cortex-M based MCUs, and is the only product that offers improved code generation while maintaining full compatibility with industry-standard GNU tools. What’s more, the extension enhances Atmel Studio 7 by enabling superior quality C and C++ code generation, resulting in reduced flash requirement for applications, faster code execution and reduced power consumption. DRT installs as an alternate toolchain, seamlessly replacing the Atmel GNU tools, making SOMNIUM’s patented-resequencing optimizations available to Atmel Studio users without complex software rewriting and staff retraining.

Unlike traditional tools which only consider the ARM Cortex processor, DRT is aware of the coupling of the processor and its memory system, automatically applying a new series of device-specific optimizations. DRT analyzes the whole program, identifying all instruction and data sequences and the interactions between them. Knowledge of the Atmel SMART MCU’s memory system and ARM Cortex pipeline are used to intelligently resequence your program.

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“By adding the SOMNIUM DRT to Atmel’s software and tools ecosystem, our developers can take their projects to market with improved code generation,” explained Henrik Flodell, Atmel Senior Product Marketing Manager, Development Tools. “With access to high-quality tools, developers can optimize memory-constrained systems for performance along with power efficiency. SOMNIUM’s advanced technology brings additional value to our customers in these areas.”

Interested? A 21-day trial of the SOMNIUM DRT Atmel Studio Extension can be be downloaded free of charge from the Atmel Gallery. An annual license with full commercial support is also available from SOMNIUM for $750.

MIT is developing shape-shifting interfaces


Thanks to MIT’s Tangible Media Group, interfaces that bend, hinge and curl will soon be a reality. 


Imagine if your iPad case automatically lifted up each time you received a message, or your Post-It notes folded down as you checked an item off your to-do list. Well, that may soon be a reality thanks to a team from MIT’s Tangible Media Group who has unveiled a technology for the rapid digital fabrication of customized thin-film shape-changing interfaces.

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By combining the thermoelectric characteristics of copper with thermally sensitive polyethylene, the researchers were able to actuate the shape of the flexible circuit composites directly. The development of UniMorph can be broken down into a few steps, which begins with designing a digital model of the pattern in CadSoft EAGLE or Adobe Illustrator and then fabricating the structure using a standard printer, copper etching, hydrogen peroxide and hyrdochloric acid — the entire process is explained in great detail here.

The base of the interface is made up of two thin layers of material: Kapton on top, plastic polyethylene on the bottom. When these are heated up either using a third layer of copper conduits or exposure to light, they expand at different rates. This will cause the bottom layer to pull up the edges of the top, thereby creating a curling effect.

Layer Composition

Passive actuation can leverage access heat, like that given off from a lightbulb or the sun, to create simple shape transformations. Meanwhile, more complex and active shape-actuation can be achieved by designing resistive heating patterns into a flexible circuit. The uniMorph composite also allows for the embedding of additional electronics such as sensors, LEDs and MCUs.

Not only can the film bend, curl, twist and open like a flower, but uniMorph’s unique capabilities unlock the potential for things like the aforementioned smart Post-It notes and iPad covers, as well as responsive bookmark/reading lights that bend into place as you navigate the page.

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According to Creative Applications, the listed examples each run on custom Arduino-compatible boards, and in some cases, the flexible circuits are produced in such a way that the ATmega328P can be soldered right on top. Intrigued? You can read all about the project in its paper here, or simply check out its video below.

Secured SAMA5D4 for industrial, fitness or IoT display


To target applications like home automation, surveillance camera, control panels for security, or industrial and residential gateways, high DMIPS computing is not enough.


The new SAMA5D4 expands the Atmel | SMART Cortex-A5-based family, adding a 720p resolution hardware video decoder to target Human Machine Interface (HMI), control panel and IoT applications when high performance display capability is required. Cortex-A5 offers raw performance of 945 DMIPS (@ 600 MHz) completed by ARM NEON 128-bit SIMD (single instruction, multiple data) DSP architecture extension. To target applications like home automation, surveillance camera, control panels for security, or industrial and residential gateways, high DMIPS computing is not enough. In order to really make a difference, on top of the hardware’s dedicated video decoder (H264, VP8, MPEG4), you need the most complete set of security features.

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Whether for home automation purpose or industrial HMI, you want your system to be safeguarded from hackers, and protect your investment against counterfeiting. You have the option to select 16-b DDR2 interface, or 32-b if you need better performance, but security is no longer just an option. Designing with Atmel | SMART SAMA5D4 will guarantee secure boot, including ARM Trust Zone, encrypted DDR bus, tamper detection pins and secure data storage. This MPU also integrates hardware encryption engines supporting AES (Advanced Encryption Standard)/3DES (Triple Data Encryption Standard), RSA (Rivest-Shamir-Adleman), ECC (Elliptic Curves Cryptography), as well as SHA (Secure Hash Algorithm) and TRNG (True Random Number Generator).

If you design fitness equipment, such as treadmills and exercise machines, you may be more sensitive to connectivity and user interface functions than to security elements — even if it’s important to feel safe in respect with counterfeiting. Connectivity includes gigabit and 10/100 Ethernet and up to two High-Speed USB ports (configurable as two hosts or one host and one device port) and one High Speed Inter-Chip Interface (HSIC) port, several SDIO/SD/MMC, dual CAN, etc. Because the SAMA5D4 is intended to support industrial, consumer or IoT applications requiring efficient display capabilities, it integrates LCD controllers with a graphics accelerator, resistive touchscreen controller, camera interface and the aforementioned 720p 30fps video decoder.

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The MCU market is highly competitive, especially when you consider that most of the products are developed around the same ARM-based family of cores (from the Cortex-M to Cortex-A5 series). Performance is an important differentiation factor, and the SAMA5D4 is the highest performing MPUs in the Atmel ARM Cortex-A5 based MPU family, offering up to 945 DMIPS (@ 600 MHz) completed by DSP extension ARM NEON 128-bit SIMD (single instruction, multiple data). Using safety and security on top of performance to augment differentiation is certainly an efficient architecture choice. As you can see in the block diagram below, the part features the ARM TrustZone system-wide approach to security, completed by advanced security features to protect the application software from counterfeiting, like encrypted DDR bus, tamper detection pins and secure data storage. But that’s not enough. Fortunately, this microprocessor integrates hardware encryption engines supporting AES/3DES, RSA, ECC, as well as SHA and TRNG.

The SAMA5 series targets industrial or fitness applications where safety is a key differentiating factor. If security helps protecting the software asset and makes the system robust against hacking, safety directly protects the user. The user can be the woman on the treadmill, or the various machines connected to the display that SAMA5 MCU pilots. This series is equipped with functions that ease the implementation of safety standards like IEC61508, including a main crystal oscillator clock with failure detector, POR (power-on reset), independent watchdog timers, write protection register, etc.

Atmel-SMART-SAMA5D4-ARM-Cortex-MPU-AtmelThe SAMA5D4 is a medium-heavier processor and well suited for IoT, control panels, HMI, and the like, differentiating from other Atmel MCUs by the means of performance and security (not to mention, safety). The ARM Cortex-A5 based device delivers up to 945 DMIPS when running at 600 MHz, completed by DSP architecture extension ARM NEON 128-bit SIMD. The most important factor that sets the SAMA5D4 apart from the rest is probably its implemented security capabilities. These will protect OEM software investments from counterfeiting, user privacy against hacking, and its safety features make the SAMA5D4 ideal for industrial, fitness or IoT applications.


This post has been republished with permission from SemiWiki.com, where Eric Esteve is a principle blogger as well as one of the four founding members of the site. This blog first appeared on SemiWiki on October 6, 2015.

IoT, digital mesh and smart machines among Gartner’s top tech trends


A look at the 10 technology trends that Gartner believes will be strategic for organizations in 2016.


During its annual Symposium/ITxpo, Gartner reveals the top 10 technology trends that will be strategic for organizations to implement in the coming months. This year, you’ll once again notice some rather familiar names on the recently-revealed list, along with a few newcomers that are expected to have an impact on the enterprise in 2016. According to the research firm, these notable trends include the Internet of Things (of course!), the Information of Everything, 3D printing and digital mesh.

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Let’s take a closer look…

The Device Mesh

The device mesh refers to an expanding set of endpoints people use to access applications and information or interact with people, social communities, governments and businesses. Think of it as the glue between the countless mobile, wearable, consumer, home, automotive and environmental devices that make up the IoT.

Ambient User Experience

The device mesh creates the foundation for a new continuous and ambient user experience. Immersive environments delivering augmented and virtual reality hold significant potential but are only one aspect of this experience, which seamlessly flows across a shifting set of devices and interaction channels blending physical, virtual and electronic environment as the user moves from one place to another.

3D Printing Materials

Advances in the next-gen technology have already paved the way for 3D printers to spit out a range of materials, including everything from carbon fiber and glass to conductive ink and electronics. These innovations are driving user demand, as the practical applications for such equipment begins to expand into more sectors. According to Gartner, the extensive lineup of 3D-printable materials will drive a CAGR of 64.1% for enterprise 3D printer shipments through 2019.

Information of Everything

More devices, more information. Everything in the digital mesh produces, uses and transmits information. And this goes well beyond just textual, audio and video, but encompasses sensory and contextual as well. The so-called “Information of Everything” will address this influx with strategies and technologies that link data from all these different sources. As the research firm puts it, information has always existed everywhere but has often been isolated, incomplete, unavailable or unintelligible; now, the advent of semantic tools and other emerging techniques will finally give proper meaning to it all.

Advanced Machine Learning

In advanced machine learning, deep neural nets (DNNs) move beyond classic computing and information management to create systems that can autonomously learn to perceive the world — all on their own. The explosion of data sources and complexity of information makes manual classification and analysis infeasible and uneconomic. DNNs automate these tasks and make it possible to address key challenges related to the information of everything trend. This area is rapidly evolving, and organizations must assess how they can apply these technologies to gain the competitive edge.

Autonomous Agents and Things

Machine learning gives rise to a spectrum of smart machine implementations, which includes robots, autonomous vehicles and virtual personal assistants, that act in an autonomous (or at least semi-autonomous) manner. While advances in physical smart machines such as robots receive some mainstream attention, the software-based smart machines have a more near-term and broader impact. In fact, VPAs like Google Now, Microsoft’s Cortana and Apple’s Siri are becoming smarter and are precursors to autonomous agents. The emerging notion of assistance feeds into the ambient user experience in which an autonomous agent becomes the main user interface. Instead of interacting with menus, forms and buttons on a smartphone, the user speaks to an app, which is really an intelligent agent.

Adaptive Security Architecture

The complexities of digital business and the algorithmic economy combined with an emerging “hacker industry” significantly increase the threat surface for an organization. Relying on perimeter defense and rule-based security is inadequate, especially as organizations exploit more cloud-based services and open APIs for customers and partners to integrate with their systems. Gartner points out that IT leaders must focus on detecting and responding to threats, along with more traditional blocking and other measures to prevent attacks. Application self-protection, as well as user and entity behavior analytics, will help fulfill the adaptive security architecture.

Advanced System Architecture

The digital mesh and smart machines require intense computing architecture demands to make them viable for organizations. Providing this required boost are high-powered and ultraefficient neuromorphic architectures. Fueled by field-programmable gate arrays (FPGAs) as an underlining technology for neuromorphic architectures, there are significant gains to this architecture, such as being able to run at speeds of greater than a teraflop with high-energy efficiency.

Mesh App and Service Architecture

Monolithic, linear application designs are giving way to a more loosely coupled integrative approach: the apps and services architecture. Bringing mobile and IoT elements into the app and service architecture creates a comprehensive model to address back-end cloud scalability and front-end device mesh experiences. Looking ahead, application teams must devise new modern architectures to deliver agile and flexible cloud-based applications with dynamic user experiences that span the digital mesh.

IoT Platforms

The Internet of Things will play an integral role in the digital mesh and ambient user experience, and the emerging and dynamic world of  IoT platforms is what makes them possible.

You can check out each of Gartner’s 10 predictions in-depth here.