Windows 10: Intel and Arm IoT Vision to Securely Connect 'Any Device to Any Cloud'

Brink · Oct 15, 2018

Uniting IoT Device Ecosystems and Enabling Dynamic Singular Provisioning Model

The Internet of Things (IoT) is transitioning from first proof-of-concept deployments into a new growth phase that is expected, according to industry analysts, to deploy 1 trillion devices by 2035. What is driving these lofty projections are the incredible business benefits that will be achieved with data-driven IoT initiatives such as edge computing, artificial intelligence (AI), predictive maintenance and autonomous systems. The more data that is collected, the more valuable the data becomes. However, this model may not be realized unless the industry can collaborate on more open and scalable methods to securely provision devices and their data to the cloud.

To answer these challenges, Intel is teaming up with Arm* to provide solutions to securely onboard both Intel and Arm IoT devices to any application or cloud framework.

First, let me walk you through the traditional manual onboarding process for IoT devices, which has multiple challenges. It typically takes more than 20 minutes per device and involves coordination among installation technicians, IT network/security operations and operational technology teams. The device identity and network access credentials are either painstakingly preloaded into the device at manufacturing or configured in the field from a standard image using insecure human processes. Compounding the security issues are the proliferation of cloud-specific provisioning methods without a consistent hardware-protected device identity model. For IoT to scale to a trillion devices in less than two decades, this process must be faster, safer and more flexible.

Now, the solution: Last October, Intel® Secure Device Onboard was launched as the first solution that enabled a “late binding” approach to provisioning, where customers could dynamically discover their target cloud platform for provisioning seconds after the device is powered on in the field. The collaboration with Arm aims to extend this capability from Intel devices to include the Arm devices that commonly are deployed together by customers. This strategic collaboration of two major ecosystems is designed to provide the industry with a more flexible provisioning method that can be natively enabled in devices.

So how does it work? Watch the prototype video below that shows how Intel and Arm devices can be credentialed and provisioned in seconds to join any cloud application framework.

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As a result, customers should be able to choose their onboarding systems of record without being locked into a single cloud provider’s provisioning method or a single device architecture. Flexibility can be built in before the device is purchased to onboard into any cloud ecosystem. Device management systems such as Pelion*, cloud/on-premise IoT platforms and connected partner ecosystems all benefit from increased variety of devices, lower cost and faster deployment. Device suppliers can simplify manufacturing to a single SKU that can be provisioned with customer-specific credentials in the field rather than in the factory, dramatically reducing cost while decreasing time to market.

“Intel and Arm are simplifying one of IoT’s most complex and challenging barriers with regard to streamlining the manufacturing and security deployment workflows for IoT. This is an ROI win for the customer, who will be able to deploy both Intel- and Arm-based devices at a lower cost and with less friction between IT and OT, while at the same time retaining flexibility over their data and cloud partner choice until the deployment phase,” said Michela Menting, director, ABI Research.

Learn more about the solution at IoT Solution World Congress’s smart building customer case study presentation and view the joint demo that is nominated for top TestBed award. You may also attend the technical presentation at Arm TechCon that will showcase the Pelion Device Management zero-touch experience. Intel and Arm are seeking customer and ecosystem feedback on the prototypes and expect to engage pilot customers later this year. Contact L: iotonboarding@intel.com for more information on the pilot programs.

Intel’s collaboration with Arm allows us to progress a joint vision of “any device, any cloud” to span multiple device architectures. As we enter this accelerated growth phase for IoT, we will continue to collaborate with technology vendors to provide customers the protections they need. On behalf of the entire Intel team, I thank our industry partners and customers for their ongoing support.

Lorie Wigle,
Vice president of Software and Services Group and general manager of Internet of Things Security at Intel Corporation.
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Source: Intel and Arm Share IoT Vision to Securely Connect "Any Device to Any Cloud" | Intel Newsroom

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Brink · Oct 15, 2018

Intel Offers Innovative Approach to IoT Scaling and Security

At the IoT Solutions World Congress, Intel addressed the challenges facing the Internet of Things (IoT) market today, and made a critical announcement designed to empower the industry to make the most of the tremendous opportunities ahead.

While earlier reports claimed that we will see 50 billion devices by 2020, the reality is we are nowhere close to reaching those numbers. In fact, recent research reports are far more tempered and predict closer to 30 billion devices in the same timeframe. The reason for the scaled-down outlook is because of the real-time issues of scaling deployments and security.

Today, provisioning and management of devices is a huge challenge, as IoT devices are added manually. It involves coordination between installation technicians, IT network operations, and operational technology teams and can typically take more than 20 minutes for a single device. Imagine installing 10,000 “smart IoT” light bulbs – at present, it could take two years to complete the process. This is to say nothing of the effort required to maintain device privacy and security.

To solve these complex issues, today Intel announced the launch of Intel® Secure Device Onboard (Intel® SDO). This technology securely automates and brings IoT devices online within seconds rather than hours. Intel SDO is being offered to IoT platform providers as a service they can provide to customers who wish to onboard thousands of connected devices.

More: Intel Secure Device Onboard (Product Brief)

Intel SDO’s “zero touch” model allows devices to dynamically discover the customer’s IoT platform account at power-on for automatic registration. It offers a one-to-many, one-time enablement solution that can be integrated into almost any device or IoT platform, thereby eliminating the need to custom pre-load provisioning configurations for each IoT implementation.

The Intel SDO also leverages Intel’s unique privacy-preserving IoT identity solution, the Intel® Enhanced Privacy ID (Intel® EPID), to anonymously authenticate the device and establish an encrypted communication tunnel, thereby preventing hackers from tracing the device from factory to owner. Intel EPID establishes a best practice identity model for IoT onboarding and is a proven method with over 2.7 billion keys distributed in Intel and non-Intel MCU processors since 2008.

Intel has expanded the availability of Intel SDO across the IoT ecosystem. Other silicon providers like Infineon, Microchip and Cypress Semiconductor will embed the EPID identity capability in their hardware. Cloud service platform and device management software providers like Google Cloud, Amazon Web Services (AWS), Microsoft Azure and Intel’s Wind River® Helix™ Device Cloud intend to provide integration to support Intel SDO’s zero touch model.

Intel SDO is now integrated with Wind River Helix Device Cloud, its device lifecycle management platform that enables IoT devices to securely connect, monitor, manage and service devices. With the integration of Intel SDO, Wind River’s latest release of Device Cloudincludes zero touch onboarding designed to mitigate the risk of security attacks to a device, ensure privacy and deliver automation that dramatically reduces installation and onboarding time to mere seconds, among other new features and capabilities.

Weatherford, a leading oil and gas services company, was part of the Intel SDO pilot program. The company wanted to pull data from existing controllers and install new wireless sensors through a gateway to the cloud to drive oil and gas insights. By adopting the Intel SDO and Wind River’s Device Cloud, Weatherford was able to create a secure, scalable oilfield ecosystem from zero-touch onboarding to continual gateway management. It projects the sheer scale of the market for managed devices could reach 290,000 wells, representing 870,000 sensor data points and nearly 10,000 IoT gateways at a global level.

With these new offerings, Intel is at the forefront of developing cutting-edge solutions to deliver on the promise of IoT’s potential.

For more details on Intel’s keynote at the IoT Solution World Congress visit Intel’s IOT Solutions World Congress page or to find our more about becoming part of the Intel SDO ecosystem, go to Intel Secure Device Onboard page.
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Source: Intel Offers Innovative Approach to IoT Scaling and Security | Intel Newsroom

Chino · Oct 15, 2018

SolidRun's MACCHIATObin ClearCloud 8K Comes with Google Cloud IoT Core Support

SolidRun, a leading developer and manufacturer of high-performance embedded solutions, and edge computing platforms, today announced support for the public beta of Google Cloud IoT Core, a fully managed service on Google Cloud Platform (GCP) to securely connect and manage IoT devices at scale. Cloud IoT Core is now publicly available to all users in beta, including new features and pricing plan. With Cloud IoT Core, businesses can easily connect and centrally manage millions of globally dispersed IoT devices. When used as part of the broader Google Cloud IoT solution, it can ingest all IoT data and connect to Google Cloud's state of the art analytics services including Cloud Pub/Sub, Dataflow, Bigtable, BigQuery, and Machine Learning.

The MACCHIATObin ClearCloud 8K, is based on a Marvell ARMADA A8040 SoC, and features a quad core Arm Cortex A-72 1.6GHz processor, including 4GB DDR4 DIMM memory (16GB optional), dual 10GbE, microSD connectors, 3 x SATA 3.0, USB 3.0 and PCIe x4 3.0 slot. SolidRun's MACCHIATObin ClearCloud 8K with Google's Cloud IoT Core allows users to easily and securely connect to GCP. The solution has been developed in collaboration with Sartura Ltd., a leading specialized open source developer and integrator for embedded applications, in conjunction with Marvell.

"It is only natural that a leading edge computing and gateway solution provider like SolidRun will complement its offering with an easy access to cloud services such as Google Cloud Platform," says Dr. Atai Ziv, SolidRun's CEO.

"With the MACCHIATObin ClearCloud 8K broadly available to customers on IoT Core, customers can gain visibility into new operational data and optimize for change in real-time," said Adam Massey, Director, Strategic Technology Partners, Google Cloud. "Together with SolidRun, we are striving to make it easier to connect, manage, and drive real business value from IOT devices."

MACCHIATObin ClearCloud 8K comes with a unique fanless GCP enclosure, and accessories for a price tag of $399.

Brink · Oct 15, 2018

Bringing intelligence to the edge with Google Cloud IoT Edge

The internet of things (IoT) presents us with enormous opportunities to positively affect the world around us—everything from increasing air quality to easing traffic to saving water and electricity. We can measure the world in new ways that can impact lives for the better.

But just as opportunities increase with IoT, so does data. IDC estimates that the total amount of data generated from connected devices will exceed 40 trillion gigabytes by 2025. This is where advanced data analytics and AI systems can help, to extract insights from all that data quickly and easily.

There are also many benefits to be gained from intelligent, real-time decision-making at the point where these devices connect to the network—what’s known as the “edge.” Manufacturing companies can detect anomalies in high-velocity assembly lines in real time. Retailers can receive alerts as soon as a shelved item is out of stock. Automotive companies can increase safety through intelligent technologies like collision avoidance, traffic routing, and eyes-off-the-road detection systems.

But real-time decision-making in IoT systems is still challenging due to cost, form factor limitations, latency, power consumption, and other considerations. We want to change that.

Bringing machine learning to the edge

Today, we’re announcing two new products aimed at helping customers develop and deploy intelligent connected devices at scale: Edge TPU, a new hardware chip, and Cloud IoT Edge, a software stack that extends Google Cloud’s powerful AI capability to gateways and connected devices. This lets you build and train ML models in the cloud, then run those models on the Cloud IoT Edge device through the power of the Edge TPU hardware accelerator.

Edge TPU is Google’s purpose-built ASIC chip designed to run TensorFlow Lite ML models at the edge. When designing Edge TPU, we were hyperfocused on optimizing for “performance per watt” and “performance per dollar” within a small footprint. Edge TPUs are designed to complement our Cloud TPU offering, so you can accelerate ML training in the cloud, then have lightning-fast ML inference at the edge. Your sensors become more than data collectors—they make local, real-time, intelligent decisions.

The Edge TPU chip, shown with a standard U.S. penny for reference

Cloud IoT Edge is the software that extends Google Cloud’s powerful data processing and machine learning capabilities to gateways, cameras, and end devices, making IoT applications smarter, more secure and more reliable. It lets you execute ML models trained in Google Cloud on the Edge TPU or on GPU- and CPU-based accelerators. Cloud IoT Edge can run on Android Things or Linux OS-based devices, and its key components are:

A runtime for gateway class devices, with at least one CPU, to locally store, translate, process, and derive intelligence from data at the edge, while seamlessly interoperating with the rest of Cloud IoT platform.

The Edge IoT Core runtime that more securely connects edge devices to the cloud, enabling software and firmware updates and managing the exchange of data with Cloud IoT Core.

The TensorFlow Lite-based Edge ML runtime that performs local ML inference using pre-trained models, significantly reducing latency and increasing the versatility of edge devices. Because the Edge ML runtime interfaces with TensorFlow Lite, it can execute ML inference on a CPU, GPU or an Edge TPU in a gateway class device, or in an end device such as a camera.

How machine learning at the edge benefits businesses

Businesses can benefit by bringing machine learning to the edge in several different ways.

Increased operational reliability

Because you can locally store, process, and derive intelligence from data at the edge, you can build robust IoT solutions on-premise, without worrying about intermittent cloud connectivity. This can be helpful for video and audio applications that require real-time processing, or use cases where devices can’t reliably connect to an external network or the internet.

Faster real-time predictions

By running on-device machine learning models, Cloud IoT Edge with Edge TPU provides significantly faster predictions for critical IoT applications than general-purpose IoT gateways—all while ensuring data privacy and confidentiality. Plus, Cloud IoT Edge and Edge TPU have been extensively tested to natively run open source reference models like MobileNet and Inception V3.

Increased security for devices and data

Cloud IoT Edge can process and analyze images, videos, gestures, acoustics, and motion locally on edge devices, instead of needing to send raw data to the cloud and then wait for a response. This local processing addresses certain industry-specific compliance needs and reduces data privacy risks. And Cloud IoT Edge uses a JSON Web Token to authenticate edge devices so that the private key never leaves the device.

Introducing the Edge TPU development kit

To jump-start development and testing with the Edge TPU, we’ve built a development kit. This kit includes a system on module (SOM) that combines Google’s Edge TPU, a NXP CPU, Wi-Fi, and Microchip’s secure element in a compact form factor. It’ll will be available to developers this October. To request early access to the Edge TPU development kit, sign up via this form.

The Edge TPU development kit—SOM (above) and base board (below)

We’re also working with our IoT ecosystem partners to develop intelligent devices that take advantage of Google Cloud IoT innovations at the edge. Semiconductor partners will create the SOM with the Edge TPU chip inside. Device makers will make industrial IoT gateways—like the kind used in factories, locomotives, oil rigs, and more—that include the SOM and Edge TPU.
Partners we're working with include:

Semiconductor companies: NXP, ARM

Gateway device makers: Accton, Harting, Hitachi Vantara, Nexcom, Nokia

Edge computing: ADLINK Technology, Kelvin, Olea Edge Analytics, Smart Catch, Trax

What our customers are saying

“Our Intelligent Vision Inspection solution enables us to deliver enhanced quality and efficiency in the factory operations of various LG manufacturing divisions. With Google Cloud AI, Google Cloud IoT Edge, and Edge TPU, combined with our conventional MES systems and years of experience, we believe Smart Factory will become increasingly more intelligent and connected,” says Shingyoon Hyun, the CTO of LG CNS. “With Intelligent Vision Inspection, we are eager to make a better working place, raise the quality of product, and save millions of dollars each year. Google Cloud AI and IoT technologies with LG CNS expertise make this possible.”

"Smart Parking enables our customers to deploy and manage frictionless parking services for both on-street and off-street situations. We are very excited about our ability to use Cloud IoT Edge and Edge TPU for building ML-enabled parking experiences for our customers,” says John Heard, CTO of Smart Parking. “At Smart Parking, our mission is to re-invent the parking experience for every solution user. The introduction of Cloud IoT Edge, Google Cloud IoT enables us to deliver on this promise in new ways within our SmartSpot gateway products.”

“At XEE, we’re working to make driving simpler, safer and more economical through our connected car platform,” explains Romain Crunelle, CTO at XEE. “Cloud IoT Edge and Edge TPU will help us to address use cases such as driving analysis, road condition analysis, and tire wear and tear in real time and in a much more cost efficient and reliable way. Enabling accelerated ML inference at the edge will enable the XEE platform to analyze images and radar data faster from the connected cars, detect potential driving hazards and alert drivers with real-time precision."

"Trax is helping retailers build a sound foundation for digital transformation,” says David Gottlieb, General Manager, Global Retail at Trax. “Cloud IoT Edge and Edge TPU will help address critical use cases such as improving on shelf availability (OSA), optimizing click-and-collect processes, and modernizing the shopping experience. This Google technology will enable accelerated machine learning at the edge—in-store images are captured and flowed through the Trax platform, where those digitized shelf images are analyzed at an increasingly faster rate providing retailers with the agility to both respond to issues in real time and to consistently delight shoppers.”

Getting started

Cloud IoT Edge, Edge TPU and Cloud IoT Core are opening up completely new possibilities with IoT. With powerful data processing and ML capabilities at the edge, devices such as robotic arms, wind turbines and smart cars can now act on the data from their sensors in real time and predict outcomes locally. For IoT, this is the future—and we can’t wait to see what you build with Google Cloud IoT.
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Source: Bringing intelligence to the edge with Cloud IoT

Windows 10: Intel and Arm IoT Vision to Securely Connect 'Any Device to Any Cloud'

Intel and Arm IoT Vision to Securely Connect 'Any Device to Any Cloud'

Intel and Arm IoT Vision to Securely Connect 'Any Device to Any Cloud'

Intel and Arm IoT Vision to Securely Connect 'Any Device to Any Cloud'

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