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Microsoft and Nokia collaborate to accelerate digital transformation and Industry 4.0 for communications service providers and enterprises

Companies announce their first joint solutions combining Microsoft cloud, AI and machine learning expertise with Nokia’s leadership across mission-critical networking and communications

REDMOND, Wash., and ESPOO, Finland Nov. 5, 2019 Microsoft and Nokia today announced a strategic collaboration to accelerate transformation and innovation across industries with cloud, Artificial Intelligence (AI) and Internet of Things (IoT). By bringing together Microsoft cloud solutions and Nokia’s expertise in mission-critical networking, the companies are uniquely positioned to help enterprises and communications service providers (CSPs) transform their businesses. As Microsoft’s Azure, Azure IoT, Azure AI and Machine Learning solutions combine with Nokia’s LTE/5G-ready private wireless solutions, IP, SD-WAN, and IoT connectivity offerings, the companies will drive industrial digitalization and automation across enterprises, and enable CSPs to offer new services to enterprise customers.

BT is the first global communications service provider to offer its enterprise customers a managed service that integrates Microsoft Azure cloud and Nokia SD-WAN solutions. BT customers can access this through a customer automated delegated rights service, which enables BT to manage both the customer Azure vWAN and the unique Agile Connect SD-WAN, based on Nokia’s Nuage SD-WAN 2.0.

“Bringing together Microsoft’s expertise in intelligent cloud solutions and Nokia’s strength in building business and mission-critical networks will unlock new connectivity and automation scenarios,” said Jason Zander, executive vice president, Microsoft Azure. “We’re excited about the opportunities this will create for our joint customers across industries.”

“We are thrilled to unite Nokia’s mission-critical networks with Microsoft’s cloud solutions,” said Kathrin Buvac, President of Nokia Enterprise and Chief Strategy Officer. “Together, we will accelerate the digital transformation journey towards Industry 4.0, driving economic growth and productivity for both enterprises and service providers.”

The cloud and IoT have ushered in the fourth industrial revolution, or Industry 4.0, wherein enterprises are embracing data to automate and streamline processes across all aspects of their businesses. By joining forces, the two companies are bringing solutions to market that will simplify and accelerate this journey for enterprises, as well as enable CSPs to play a key role in helping their customers realize the potential of industrial digitalization and automation while also optimizing and better differentiating their own businesses.

Accelerating digital transformation for enterprises

Microsoft and Nokia are partnering to help accelerate digital transformation for enterprises by offering connectivity and Azure IoT solutions that unlock connected scenarios across multiple industries including digital factories, smart cities, warehouses, healthcare settings, and transportation hubs such as ports, airports and more.

The Nokia Digital Automation Cloud (Nokia DAC) 5G-ready industrial-grade private wireless broadband solution with on-premise Azure elements will enable a wide variety of secure industrial automation solutions that require more reliable connectivity, efficient coverage and better mobility than traditional Wi-Fi networks provide. For example, connected smart tools and machines on manufacturing floors that enable increased productivity, flexibility and safety for workers, or autonomous vehicles and robots in industrial environments that improve automation, efficiency and overall safety.

Enabling new enterprise services offered by service providers

Nokia’s Nuage SD-WAN 2.0 solution now enables service providers to offer integration with Microsoft Azure Virtual WAN for branch to cloud connectivity, with the companies planning to offer more options for branch internet connectivity in 2020. By automating branch and hybrid WAN connectivity, enterprises will have simplified, faster access to cloud applications such as Office 365, integrated security from branch-to-branch and branch-to-Azure and reduced risk of configuration errors causing security or connectivity issues.

Furthermore, the companies are integrating Nokia’s Worldwide IoT Network Grid (WING) with Azure IoT Central to make the onboarding, deployment, management and servicing of IoT solutions seamless. This integration provides CSPs with the opportunity to offer their enterprises a single platform including vertical solutions to enable secure connected IoT services, such as asset tracking and machine monitoring on a national or global scale. Enterprises will be able to use Azure IoT Central and partner solutions for faster and easier enablement and implementation of their IoT applications together with Nokia’s IoT connectivity solutions.

Driving digital transformation for CSPs

Microsoft and Nokia are collaborating to host Nokia’s Analytics, Virtualization and Automation (AVA) cognitive services solutions on Azure. These AI solutions will enable CSPs to move out of private data centers and into the Azure cloud to realize cost savings and transform operations for 5G. Predictive Video Analytics is an example of a joint solution that will ensure optimal video experiences for CSP subscribers, improving reliability by up to 60 percent.

About Microsoft

Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.

About Nokia

We create the technology to connect the world. We develop and deliver the industry’s only end-to-end portfolio of network equipment, software, services and licensing that is available globally. Our customers include communications service providers whose combined networks support 6.1 billion subscriptions, as well as enterprises in the private and public sector that use our network portfolio to increase productivity and enrich lives.

Through our research teams, including the world-renowned Nokia Bell Labs, we are leading the world to adopt end-to-end 5G networks that are faster, more secure and capable of revolutionizing lives, economies and societies. Nokia adheres to the highest ethical business standards as we create technology with social purpose, quality and integrity. www.nokia.com

For more information, press only:

Microsoft Media Relations, WE Communications for Microsoft, (425) 638-7777, rrt@we-worldwide.com

Nokia Communications, +358 10 448 4900, press.services@nokia.com

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The Internet of Things is going mainstream, Microsoft survey finds

“We wanted to find new ways to use IoT sensor technology to make a building interact with the facility manager and the owner,” says Michael Cesarz, chief executive officer for MULTI at thyssenkrupp Elevator. “thyssenkrupp is uniquely positioned to do that, because an elevator is the nervous system of a building, and the shafts are like the backbone – they are a crucial structural element and they touch every single floor and serve every single tenant.”

To help develop new solutions in the Innovation Test Tower, thyssenkrupp partnered with Willow, a member of the Microsoft Partner Network. thyssenkrupp uses the company’s Willow Twin platform powered by Azure IoT which provides a “digital twin” of the tower that delivers actionable insights to the building managers.

Starbucks

Each Starbucks store has more than a dozen pieces of equipment, from coffee machines to grinders and blenders, that must be operational around 16 hours a day. A glitch in any of those devices can mean service calls that rack up repair costs. More significantly, equipment problems can potentially interfere with Starbucks’ primary goal of providing a consistently high-quality customer experience.

“Any time we can create additional moments of connection between our partners and customers, we want to explore and activate,” says Natarajan “Venkat” Venkatakrishnan, vice president of global equipment for Starbucks. “Our machines are what allow our partners to create that special beverage, and ensuring they are working properly is critical.”

To reduce disruptions to that experience and securely connect its devices in the cloud, Starbucks is partnering with Microsoft to deploy Azure Sphere, designed to secure the coming wave of connected IoT devices across its store equipment.

A smart phone displays personalized recommendations to customers via a mobile app.
Starbucks is delivering personalized recommendations to customers via its mobile app and, soon, its drive-thrus. (Photo courtesy of Starbucks)

The IoT-enabled machines collect more than a dozen data points for every shot of espresso pulled, from the type of beans used to the coffee’s temperature and water quality, generating more than 5 megabytes of data in an eight-hour shift. Microsoft worked with Starbucks to develop an external device called a guardian module to connect the company’s various pieces of equipment to Azure Sphere in order to securely aggregate data and proactively identify problems with the machines.

The solution will also enable Starbucks to send new coffee recipes directly to machines, which it has previously done by manually delivering the recipes to stores via thumb drive multiple times a year. Now the recipes can be delivered securely from the cloud to Azure Sphere-enabled devices at the click of a button.

“Think about the complexity — we have to get to 30,000 stores in nearly 80 markets to update those recipes,” says Jeff Wile, senior vice president of retail and core technology services for Starbucks Technology. “That recipe push is a huge part of the cost savings and the justification for doing this.”

Bühler

Just one grain of corn infected with a highly carcinogenic mold called aflatoxin can be all it takes to poison the whole harvest and sicken or even kill people and animals, not to mention the waste of having to throw out the lot when contamination isn’t found in time. Aflatoxin often can’t be seen, smelled or tasted, and it’s not destroyed by heat – so cooking contaminated food doesn’t make it safe.

Ingestion of high levels of aflatoxin can be fatal, and chronic exposure can result in serious health problems, according to the International Food Policy Research Institute. There are about 155,000 new cases a year of cancer caused by aflatoxin – it’s the leading cause of liver cancer in developing countries.

A Bühler engineer is fighting aflatoxin in corn by combining new camera and UV lighting technology.
Bühler engineers are fighting aflatoxin in corn by combining new camera and UV lighting technology, shown here being assembled. (Photo courtesy of Bühler)

Since consumers can’t tell if their food is infected, the onus is entirely on growers, harvesters and processors – more of whom are having to fight the mold as it expands north amid climate change that stresses crops and makes them more susceptible. So the stakes are high for the new corn processing system Bühler engineers developed as part of an innovation challenge.

With the LumoVision optical sorter, corn gets fed from a truck into a hopper above the 6-foot-tall machine, and a vibratory feeder sends it into a chute where it accelerates to 3.5 meters (11.5 feet) a second as it flows in a single layer. UV lights illuminate the corn. A camera on each side of the chute monitors the lighted grains, looking for the telltale fluorescence of aflatoxin infection.

High-speed valves operating compressed air jets – which can open or close in a thousandth of a second – simply shoot any contaminated kernels into the rejects bin, letting the rest of the healthy corn pass through into storage or shipping containers.

Weather patterns at the time of harvest, the health of other lots harvested in the area and other relevant data points can be uploaded to the Bühler Insights platform hosted on the Microsoft cloud to augment the machine data. This can then be combined with information from the cameras as they watch the grains pass by, monitored and analyzed using IoT and edge computing to provide a real-time risk assessment on the crop and guide the system’s processes. If the risk is minimal, sorting can be paused while monitoring continues. If the risk rises, sorting automatically restarts.

“This came at exactly the right time for us, because we were just starting our digital journey toward data analytics and the Internet of Things,” says Stuart Bashford, Bühler’s digital officer. “The general concept for something like this had been around for years, but the technology never existed before to make it commercially viable. But now it’s all come together in this incredibly rewarding project.”

Chevron

Deep within a Chevron fuel refinery, one key machine is now talking – and revealing secrets about its own health.

That chatty piece of equipment, called a heat exchanger, removes the heat from fluids flowing through it as part of the plant’s fuel processing.

A heat exchanger affixed with cloud-connected sensors.
A heat exchanger affixed with cloud-connected sensors. (Photo courtesy of Chevron)

In a pilot program, Chevron affixed some exchangers with wireless, Industrial Internet of Things (IIoT) sensors that collect and send real-time data from the heat exchanger to the cloud – supplementing information already gathered by the safety and control system.

Data scientists then analyze that fresh data to check the equipment’s health status now, and to predict its condition in the future.

“Understanding the health of these exchangers can prevent unscheduled outages as well as optimize when we clean these units,” says Deon Rae, a Chevron fellow and lead of Chevron’s IIoT Center of Excellence. “That has the potential to save the company millions of dollars a year when scaled across our whole inventory of heat exchangers.”

The company plans to expand that same IoT technology to other pieces of equipment at facilities around the world to similarly monitor their health and forecast their performance, Rae says. Chevron has more than 5,000 heat exchangers in active operations in more than 100 countries. Deploying health monitoring across different pieces of equipment has the potential to provide significant savings.

Toyota Material Handing Group

Toyota Material Handling Group is the largest forklift manufacturer in the world, but its customers require much more than warehouse trucks and equipment. To better serve them, the global business is expanding and enriching its logistics solutions with digital innovation and Toyota’s renowned principles in lean and efficient manufacturing.

By providing solutions with artificial intelligence, mixed reality and IoT, Toyota Material Handling Group is helping customers meet the global rise in e-commerce and move goods quickly, frequently, accurately and safely.

Workers ride forklifts in a warehouse.
Toyota Material Handling Group forklifts. (Photo courtesy of Toyota Material Handling Group)

With Microsoft technologies, the solutions range from connected forklift and field service systems available today to AI-powered concepts that pave the way for intelligent automation and logistics simulation – all designed with Toyota’s standards for optimizing efficiency, operation assistance and kaizen, or continuous improvement.

“Our direction is going to more systemizing and logistics solutions, services in digital automation, AI analytics and IoT,” says Toshihide Itoh, associate director and CIO of Toyota Material Handling Group, an Aichi, Japan-based division of Toyota Industries Corporation. “We also continue to improve our forklift trucks, because this is our origin. But customers need more and more efficient logistics and we need digital innovation to accelerate and expand our business.”

Toyota has presented its vision for a future warehouse with lean logistics and pre-trained, intelligent forklifts. Enabled with machine learning and IoT services in Microsoft Azure, the vehicles can quickly learn navigation in a virtual model of a customer’s warehouse, a so-called “digital twin.” Customers can experience the trucks interacting with their physical and virtual environment.

The ability to simulate and visualize a physical environment will help solve one of the biggest challenges in the industry: the long deployment time for customized IoT solutions. Installations can normally take six months to a year, but using machine learning and digital twins can significantly shorten the time.

Electrolux

Numerous studies have shown that bad air outside affects air quality inside homes and offices, entering through ventilation systems.

Even worse, pollutants generated inside from cleaning supplies, cooking and fireplaces can be even harder on your health than what you breathe out on the street, according to the Environmental Protection Agency.

A smartphone displays an app for the Pure A9, offering real-time data, including the state of indoor air quality.
An app for the Electrolux Pure A9 offers real-time data, including the state of indoor air quality. (Photo courtesy of Electrolux)

The Pure A9 – an IoT-connected air purifier built with Microsoft Azure – removes ultra-fine dust particles, pollutants, bacteria, allergens and bad odors from indoor rooms. It launched March 1 in four Nordic countries plus Switzerland and, previously, in Korea.

By linking the purifier and its associated app to the cloud, Electrolux can show the product’s users real-time data about their air quality – inside and outside – while tracking interior air improvement over time. In addition, the Pure A9 continuously monitors its filter usage, alerting users when it’s time to order a replacement filter.

And as a connected appliance, the Pure A9 eventually may have the ability to learn the daily patterns of when household occupants are typically away, enabling the device to run itself on a smart schedule, Larsson says.

“If we can predict when the house is empty, we make sure not to waste filter by cleaning air that nobody is going to breathe,” says Andreas Larsson, engineering director at Electrolux. “Then we can start the purification, so the air is clean when you come home.”

Visit the Official Microsoft Blog to read more from the survey’s breakdown of IoT trends.

Top photo: Starbucks partners are able to spend more time hand-crafting the perfect beverage and less time on machine maintenance thanks to cloud-connected devices. (Photo courtesy of Starbucks) 

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SK Telecom and Microsoft sign MOU for comprehensive cooperation in cutting-edge ICT

The two companies agreed to combine their strengths to jointly promote IoT business, AI technologies and services, media and entertainment services, and new ways of working

Park Jung Ho, CEO of SK Telecom (left), and Satya Nadella, CEO of Microsoft (right), at a recent meeting.
Park Jung Ho, CEO of SK Telecom (left), and Satya Nadella, CEO of Microsoft (right), at a recent meeting.

SEOUL, KOREA – May 13, 2019 – SK Telecom (NYSE:SKM) and Microsoft Corp. signed a memorandum of understanding (MOU) on May 7 for comprehensive cooperation in leading-edge ICT, including 5G, artificial intelligence (AI) and cloud.

Under the MOU, SK Telecom and Microsoft will combine their technological capabilities in areas such as 5G, AI and cloud to jointly promote Internet of Things (IoT) business including smart factory; AI technologies and services; media and entertainment services; and new ways of working for ICT companies under the SK Group umbrella.

To promote smart factory IoT business operations, the two companies established a business strategic partnership in February 2019 to launch Microsoft Azure with Metatron, SK Telecom’s self-developed big data solution. SK Telecom and Microsoft will work together to further upgrade the service and implement joint marketing activities.

By putting together the capabilities of SK Telecom’s AI platform NUGU with Microsoft’s Cortana digital assistant, the two companies will work together to offer new AI-powered products and services, including consumer solutions such as smart speakers and other offerings for the enterprise.

Moreover, the two companies will work together to create a new level of customer experience in the field of media and entertainment.

SK Telecom will adopt Microsoft 365, the company’s intelligent and secure solution to empower employees, to create a modern workplace and promote a new way of working among employees. Eventually, SK Telecom will expand Microsoft 365 to other ICT companies under the SK Group umbrella. In addition, the two companies will provide new value to customers by combining Microsoft’s modern workplace devices and solutions, such as Surface and Office 365, with SK Telecom’s unique products and services.

“SK Telecom is pleased to join hands with Microsoft as collaboration with global leading companies like Microsoft is essential to gain leadership in the 5G market, where competition is already fierce,” said Park Jung-ho, President and CEO of SK Telecom. “SK Telecom will work closely with Microsoft to create an unprecedented value by combining the strengths and capabilities of the two companies.”

“Through the strategic partnership with SK Telecom, we will play a key role in shaping the future and accelerating the digital transformation of the telecommunications industry with our world-class network and technology,” said Jason Zander, executive vice president, Azure, Microsoft. “This will be a deep and multifaceted partnership that strengthens the power of cloud and AI to deliver innovative new services to customers.”

About Microsoft

Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.

About SK Telecom

SK Telecom is the largest mobile operator in Korea with nearly 50 percent of the market share. As the pioneer of all generations of mobile networks, the company has commercialized the fifth generation (5G) network on December 1, 2018 and announced the first 5G smartphone subscribers on April 3, 2019. With its world’s best 5G, SK Telecom is set to realize the Age of Hyper-Innovation by transforming the way customers work, live and play.

Building on its strength in mobile services, the company is also creating unprecedented value in diverse ICT-related markets including media, security and commerce.

For more information, press only:

SK Telecom Public Relations/Media Contact, skt_press@sk.com or sktelecom@bm.com

Microsoft Media Relations, WE Communications for Microsoft, (425) 638-7777, rrt@we-worldwide.com

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Microsoft acquires Express Logic, accelerating IoT development for billions of devices at scale

IoT sensors are being infused into just about everything, from industrial equipment to consumer devices, and increasingly these devices are connecting to the cloud. By 2020, Gartner predicts there will be more than 20 billion connected devices*. In April 2018, we announced we’re investing $5 billion in IoT and the intelligent edge over the next four years. Since then, we’ve been making a number of investments from product innovation – including Azure Sphere, Azure Digital Twins, Azure IoT Edge, Azure Maps and Azure IoT Central – new partnerships with DJI, SAP, PTC, Qualcomm and Carnegie Mellon University for IoT and edge app development, and programs to help drive the next wave of innovation for our customers.

Express Logic logoToday, I am incredibly excited to share we have acquired Express Logic, a leader in real time operating systems (RTOS) for IoT and edge devices powered by microcontroller units (MCUs). Express Logic’s ThreadX RTOS has over 6.2 billion deployments, making it one of the most deployed RTOS in the world. This widespread popularity is driven by demand for technology to support resource constrained environments, especially those that require safety and security. Manufacturers building products across a range of categories – from low capacity sensors like lightbulbs and temperature gauges to air conditioners, medical devices, and network appliances – leverage the size, safety and security benefits of Express Logic solutions to achieve faster time to market. Even highly constrained devices (battery powered and having less than 64KB of flash memory) can use Express Logic solutions. Over 9 billion of these MCU-powered devices are built and deployed globally every year, many of which can benefit from Express Logic solutions.

With this acquisition, we will unlock access to billions of new connected endpoints, grow the number of devices that can seamlessly connect to Azure and enable new intelligent capabilities. Express Logic’s ThreadX RTOS joins Microsoft’s growing support for IoT devices and is complementary with Azure Sphere, our premier security offering in the microcontroller space. Our goal is to make Express Logic’s ThreadX RTOS available as an option for real time processing requirements on an Azure Sphere device and also enable ThreadX-powered devices to connect to Azure IoT Edge devices when the IoT solution calls for edge computing capabilities. While we recommend Azure Sphere for customers’ most secured connections to the cloud, where Azure Sphere isn’t possible in highly constrained devices, we recommend Express Logic’s ThreadX RTOS over other RTOS options in the industry because of its additional certifications and out-of-the-box connectivity to Azure IoT Hub.

As we’ve stated consistently in the past, our primary goal is to simplify IoT – from the cloud all the way down to the smallest MCU based devices. We do this by meeting our customers where they are with the right developer tools, software and intelligent cloud services to manage their solutions at scale. Express Logic’s technology and team will be an incredible addition to Microsoft in our quest to give every customer the ability to transform their businesses, and the world at large, with connected solutions.

*Gartner, Inc., “Leading the IoT: Gartner Insights on how to Lead in a Connected World”, by Mark Hung https://www.gartner.com/imagesrv/books/iot/iotEbook_digital.pdf

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One Year In: How our $5B investment in IoT and intelligent edge is accelerating innovation

One year ago, we announced our commitment to invest $5B in IoT (Internet of Things) and intelligent edge – technology that is accelerating ubiquitous computing and bringing unparalleled opportunity for transformation across industries. Our commitment is to a build trusted, easy to use platform for our customers and partners to build solutions – no matter where they are starting in their IoT journey.

Our customers are embracing IoT as a core strategy to drive better business outcomes, improve safety and address social issues – from predicting and preventing equipment failures, optimizing smart buildings for space utilization and energy management and improving patient outcomes and worker safety. From the intelligent cloud to the intelligent edge, this year has been one of tremendous growth – in IoT technology portfolio, partner ecosystem and customer momentum – and we are only just beginning.

Accelerating customer innovation in IoT from cloud to edge across industries

What’s truly exciting is seeing our customers achieve real business outcomes with Azure IoT and intelligent edge-based solutions. Our IoT platform is powering customer solutions with thousands of devices, at scale, and the number of devices supported has grown nearly 150 percent year-over-year. This year, many customers such a Starbucks, Chevron, Walmart, Walgreens, BMW, Volkswagen, Toyota Material Handling Group and more are leveraging Azure as their cloud platform with IoT and AI services to accelerate their digital transformation.

Starbucks is using Azure Sphere to connect select equipment, enabling its partners (employees) more opportunity to engage with customers. This includes everything from beverage consistency, waste reduction, the management of energy consumption and predictive maintenance.

With Azure and our IoT services, Chevron is connecting a critical piece of equipment – heat exchangers, which manage the heat from fluids flowing through it as part of the plant’s fuel processing – to do predictive maintenance and ultimately prevent unscheduled outages.

In Walmart’s technology center in Austin, Texas, which is designed accelerate digital innovation, the retail leader is embracing IoT as a way to save energy and prevent product loss. Walmart is using thousands of IoT sensors on HVAC and refrigeration systems that process a billion daily data messages from stores worldwide.

As part of Microsoft’s partnership with Walgreens Boots Alliance (WBA) to make health care delivery more personal, affordable and accessible for people around the world, WBA will use a portfolio of connected IoT devices for nonacute chronic care management, delivered by Microsoft’s cloud, AI and IoT technologies.

This week with BMW Group, we announced the Open Manufacturing Platform (OMP), a new technology framework and open community to share smart factory solutions across the automotive and manufacturing sectors to significantly accelerate future industrial IoT developments.

This year Volkswagen announced a partnership with Microsoft to create the Volkswagen Automotive Cloud with Azure and Azure IoT Edge to create a seamless experience for drivers from the moment they enter, use and leave their vehicles. From 2020 onwards, more than 5 million new Volkswagen brand vehicles per year will be fully connected and will be part of the IoT cloud.

By infusing solutions with artificial intelligence, mixed reality and the IoT, Toyota Material Handling Group is providing solutions to customers meet the global rise in ecommerce, and move goods quickly, frequently, accurately and safely. With Microsoft technologies, the solutions range from connected forklift and field service systems available today to AI-powered concepts that pave the way for intelligent automation and logistics simulations – all designed with Toyota’s standards for optimizing efficiency, operation assisting and continuous improvement.

The stories continue to roll in.

New innovations in our IoT platform

In the last year, we launched more than 100 new services and features in our IoT platform, designed to make IoT solutions more secure and scalable, reduce complexity, make our platform more open and create opportunities in new market areas. Our core focus has been to address the industry challenge of securing connected devices at every layer, as well as advancing IoT to create a more seamless experience between the physical and digital worlds.

Simplifying IoT and securing IoT endpoints at scale

IoT is complex, requiring deep knowledge of cloud, security and devices, but the business benefits are significant. With Azure IoT Central, which became generally available this year, we have created a way for businesses to get started in IoT by quickly provisioning a solution in just a matter of hours and with built-in security features. With valuable data moving closer to the edge, IoT security demands a holistic approach. This year we introduced Azure Sphere, a world-class security solution for connected microcontroller devices (MCUs), which go in everything from smart-home and medical devices to equipment on the factory floor. Windows 10 IoT Core Services includes security and reliability updates for the operating system to keep device security up to date. Azure Security Center for IoT now includes support for Azure IoT services to proactively monitor IoT devices, enabling businesses to implement security best practices for detecting and mitigating threats.

Delivering spatial intelligence at scale

IoT is no longer just about connected endpoints. It’s the sum of the endpoints – the digital objects – that create a holistic solution. We see significant opportunity for our customers to use spatial intelligence to manage physical assets and spaces with digital models and mapping across smart spaces, cities and buildings. This fall, we introduced Azure Digital Twins to enable customers and partners to query data in the context of a space – rather than from disparate sensors – empowering them to build repeatable, scalable experiences that correlate data from digital sources and the physical world. Azure Maps provides developers from all industries powerful geospatial capabilities, and new MR services including Azure Spatial Anchors and Azure Remote Rendering enable customers to create precise points of interest in with mixed reality in physical space as well as enable interactive, high-quality 3D models.

Bringing AI to the edge

The proliferation of IoT devices and resulting massive amount of data requiring real-time intelligence are fueling the need to move compute and analytics closer to where the data resides. This year, we open sourced the Azure IoT Edge runtime, providing developers have even greater flexibility and control of their edge solutions, enabling them to modify the runtime and debug issues for applications at the edge. Over the past year, we added five new Azure Cognitive Services that can run locally on an edge device, and we’ve made it easier to deploy your own Azure Machine Learning models on Azure IoT Edge. We’ve also enabled high-speed inferencing at the edge with Azure Data Box Edge.

 Growing the Microsoft IoT partner ecosystem

We’re proud to have one of the largest and fastest-growing partner ecosystems with more than ten thousand IoT partners from intelligent edge to intelligent cloud. Partners are critical to our customers’ success in IoT, bringing rich domain expertise across industries so customers can see clear value to their business, as well as integration for critical apps and infrastructure to increase time to value.

This year, we announced more than 70 new partnerships in IoT, which help our customers build IoT solutions faster. At CES we announced our collaboration with Universal Electronics to launch a new digital assistant platform for the home built on Microsoft Azure using AI and IoT services. PTC announced ThingWorx Industrial Innovation Platform on Microsoft Azure to deliver a robust solution for Industrial IoT and digital product lifecycle management. At MWC, we announced new partnerships with SAP, and Cradlepoint. SAP Leonardo IoT will integrate with Azure IoT services providing our customers with the ability to contextualize and enrich their IoT data with SAP business data within SAP Leonardo IoT to drive new business outcomes. With Cradlepoint, we’re enabling customers to connect their IoT infrastructure to cloud-based applications to a global satellite communications network and to help bridge the OT and IT collaboration gap, respectively.

We’re also working with several device partners to accelerate development at the intelligent edge. With Qualcomm, we created an Azure IoT Starter Kit to enable developers vision AI solution and run their AI models on the device. With NXP, we announced the public preview for Windows 10 IoT Core with built-in Azure connectivity, to enable secure, power-optimized devices for the intelligent edge. We’re also partnering with NVIDIA and DJI to integrate third-party SDKs to simplify development and increase time to value of AI applications at the edge.

Looking ahead: Industry opportunity in IoT

We are one year into our four-year investment. Our priority over the next three years is clear: make it easy for any company to create scalable, secured IoT solutions. We partnered with Boston Consulting Group (BCG) to better understand the trends and opportunity for the industry at large. Our findings, captured in the whitepaper here, indicate IoT is moving into broad adoption and yet, some of the greatest barriers to success are not just about technology – it’s also about business strategy and executive leadership. More than 60 percent of executives we surveyed indicated these to be bigger elements of success than technology. One in four executives we surveyed indicated that their companies’ IoT initiatives underperformed expectations. The findings highlight key ingredients for a successful IoT innovation project. You’ll continue to see more announcements from us and our partners and customers to help our customers and partners in their IoT journeys. You can read more about adoption of IoT across industries in the BCG whitepaper.

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Electrolux has a smart air purifier that lets you breathe easy, even in polluted cities

Acrid smoke, carried by stiff breezes from a nearby garage fire, recently filled the Electrolux campus in Stockholm, Sweden.

Some developers and executives felt their throats burn. At least one employee had trouble breathing. She decided to leave. But before heading home, she stopped inside the building where Andreas Larsson and his team were testing the Pure A9, an IoT-connected air purifier built with Microsoft Azure.

The moment had come to see what the new device could do in dire conditions.

Andreas Larsson stands behind four Pure A9 air purifiers at Electrolux headquarters.
Andreas Larsson with some of the Pure A9 purifiers used to clear the air during the fire near Electrolux headquarters.

“We had 10 or 15 Pure A9 air purifiers and turned them all on,” recalls Larsson, engineering director at Electrolux. “That made a significant change in air quality. We asked her to come into our office, sit down and just work there. She took some deep breaths. She was happy. She stayed for the rest of the day.”

The Pure A9 – launched March 1 in four Nordic countries plus Switzerland and, previously, in Korea – removes ultra-fine dust particles, pollutants, bacteria, allergens and bad odors from indoor rooms.

By linking the purifier and its associated app to the cloud, Electrolux can show the product’s users real-time data about their air quality – inside and outside – while tracking interior air improvement over time. In addition, the Pure A9 continuously monitors its filter usage, alerting users when it’s time to order a replacement filter.

And as a connected appliance, the Pure A9 eventually may have the ability to learn the daily patterns of when household occupants are typically away, enabling the device to run itself on a smart schedule, Larsson says.

“If we can predict when the house is empty, we make sure not to waste filter by cleaning air that nobody is going to breathe,” Larsson says. “Then we can start the purification so the air is clean when you come home.”

Launch of the Pure A9 marks a fresh phase in Electrolux’s push to provide connected appliances to “millions of homes around the world, shaping living for the better for consumers,” Larsson says.

He dubs it the company’s “wellbeing journey into IoT, software products, data and apps” – a process that began two years ago with a cloud-connected, robotic vacuum called the Pure i9.

A Pure i9 robotic vacuum moves across a run toward a table and sofa.
A Pure i9 cleans a rug and flooring while navigating a table and sofa.

The triangular device is equipped with a 3-D camera for smart navigation.

Moreover, its Azure IoT platform helped get the product to market quickly while also enabling developers to update software and add features after launch, Larsson says. Newer features include a map view showing where the Pure i9 has cleaned.

The roaming robot is now available in the U.S., Europe and Asia, including China.

The Pure i9 from above on a wood floor.
The Pure i9 in action.

Cloud data from the device also led Electrolux to launch a unique trial in Sweden: vacuum-as-a-service.

Consumers in that country can buy an $8-per-month subscription to the Pure i9 and get 80 square meters of floor cleaning, Larsson says.

“You only pay for what you use,” Larsson says. “This is not possible unless it is connected to the cloud or unless we have the data. With this kind of product, we see business alternatives we’ve never been able to do before.”

That trial underscores the digital ambitions of a 100-year-old brand once known for its canister vacuums. Today, Electrolux also manufactures and sells ovens, refrigerators, washers, dryers, water heaters and an array of other household gadgetry.

An app for the Pure A9 gives users valuable data on the state of their air.Following the Pure i9’s launch in 2017, “it soon became clear that this was not going to be a one-off product,” Larsson says. “An ambitious plan to create an ecosystem of smart, networking products … started to form.”

A smartphone displays the Pure A9 app interface next to a Pure A9 air purifier.
An app for the Pure A9 offers real-time data, including the state of indoor air quality.

They chose the cloud-connected air purifier as their next connected appliance. In September 2018, a team of just three Electrolux developers began building a new Azure IoT platform for what would become the Pure A9. By February 2019, that product was already on the market in Asia.

“Azure enabled them to launch a product to the whole world with minimal development investments and in rapid pace,” says Arash Rassoulpour, a Microsoft cloud solution architect who worked with Electrolux developers on the products.

Electrolux engineers also used the ready-made functions in Azure IoT Hub, instead of writing the code themselves, saving them more development time, Larsson says.

To introduce its new air purifier to consumers, Electrolux initially launched in Korea, where staggering air pollution levels have caused what legislators describe as a “social disaster.”

A smoggy skyline in Seoul, South Korea with the sun on the horizon.
Another smoggy day in Seoul, South Korea. (Getty Images)

On March 5, the South Korean government advised residents in Seoul to wear masks and avoid walking outside due to a record level of fine dust particles in the air.

Numerous studies have shown that bad air outside affects air quality inside homes and offices, entering through ventilation systems.

Even worse, pollutants generated inside from cleaning supplies, cooking and fireplaces can be even harder on your health than what you breathe out on the street, according to the Environmental Protection Agency.

An Electrolux sign on the exterior of a building a company headquarters in Stockholm, Sweden.
Electrolux global headquarters in Stockholm, Sweden.

“By monitoring and controlling consumers’ indoor air quality, our smart, premium air purifier contributes to a better indoor climate and increased wellbeing for the consumer,” says Karin Asplund, Electrolux’s global category director for ecosystem.

“Via the Pure A9 app, the consumer can also get an increased understanding of the actual job done by the purifier thanks to its ability to turn sensor data into understandable and actionable information,” she adds.

With the first two connected appliances now in the hands of consumers, Larsson envisions how that technology can help get the weekend started on a comfy, tidy note.

“When you come home on Friday evening, our goal is to have your home clean and pure,” Larsson says. “You can just come in, take off your shoes, sit down and feel, OK, this is my home.”

Top image: A woman holding her daughter in their home, looking through a window at a view of Seoul on a day with heavy pollution in the air. (Getty Images)

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The biggest IoT stories of 2018

This blog post was authored by Peter Cooper, Senior Product Manager, Microsoft IoT.

Back in April, we announced our intention to invest $5 billion in the Internet of Things (IoT) over the next five years. The importance of this commitment has become even clearer since, as technology has already evolved, customers have innovated, and possibilities have grown. As 2018 draws to a close, here’s a look back at the topics that drove the most interest and excitement here on our blog—and a window into what’s coming for this technology in the near future.

Smart spaces

The spaces around us are coming alive with the power of data. In our post, “Smart buildings, built on Azure IoT,” we talked about how IoT and AI are helping those who own, manage, and use buildings increase efficiency to reduce cost and improve productivity. With announcements of products such as Azure Sphere and Azure Digital Twins, we empowered our partners and customers to explore new possibilities for managing and improving the built environment responsively, in real time.

Over the past year, we’ve also seen customers expand their vision of what smart spaces can do. Traditionally, these projects were heavily focused on operational aspects of building management such as infrastructure maintenance, water, and power usage. This is still the foundational use case and justification for IoT-enabled buildings, but people are increasingly excited about the transformative capabilities of smart spaces. Customers are exploring how they can use analytics to understand and optimize how people use the spaces they inhabit. Furthermore, they’re designing smart building solutions with the potential to dramatically influence day-to-day productivity and increase positive interactions.

For example, Steelcase showed how they’re creating smart and connected workplaces. As Scott Sadler, Steelcase Smart + Connected manager said, “By embedding technology into the work environment, we are enabling people to tell organizations what spaces are successful and why. We can measure and identify patterns in how and where people are working.” The ease of obtaining these insights will only increase in the coming year, and we’re thrilled to see where this field is headed. As smart space initiatives expand beyond the workplace to encompass stadiums, schools, hospitals, banks, and more—and as edge and cloud technologies connect them to the larger built environment—truly transformative possibilities are bound to emerge. 

The intelligent edge

As with smart buildings, we’ve been inspired by the visionary scope our partners and customers have for edge computing and look forward to big things in 2019. IT departments are using edge computing to solve infrastructure and security challenges to make IoT a reality. Hardware vendors are expanding the intelligence of their devices to take advantage of new functionalities. A diverse and vibrant ecosystem is arising that will push what’s possible at the edge.

We highlighted five ways edge will transform business, including reduced IoT solution costs, improved security, lower latency, greater reliability, and interoperability with legacy devices. Enabling this goodness requires a strong technology foundation, which is why the Azure IoT Edge platform garnered so much attention from the industry. Since then, the solution has moved into general availability, enabling any business to deliver cloud intelligence locally on cross-platform IoT devices.

Edge computing has depth, fueling growth in both infrastructure and IoT, which allows data processing, analytics, and advanced functionality on connected devices whether they’re connected to the cloud or not.

These innovations are many and varied. With a consistent deployment model, companies can code and test edge capabilities on any platform and launch them seamlessly. For example, some are training data models using cloud-scale machine learning engines, and then deploying those models as-is to edge devices. Others are using edge as a way to aggregate and preprocess information so that only relevant data is delivered to the cloud. Edge computing also makes it possible to build IoT solutions that are offline for extended periods of time yet deliver powerful predictive capabilities based on local data. It all adds up to more efficient, effective use of data to improve everyday lives around the world. 

Open standards and interoperability

Interoperability is a hot topic, especially in the manufacturing space, where businesses are looking for simple, comprehensive solutions that allow them to enable the connected factory with a mix of IoT-ready and legacy equipment. Our April post on OPC Unified Architecture (OPC UA) highlighted how manufacturers are using the standard to enable openness and interoperability while maintaining high standards of security.

In fact, this past year could be considered “the year of OPC UA,” with ABB, Rockwell, and Schneider Electric joining the OPC Foundation board members, alongside SIEMENS, SAP, Yokogava, Iconics, Ascolab, and, of course, Microsoft.

National industry initiatives have also continued deepening their commitment to interoperability. Germany’s Industrie 4.0 has released new testbeds and specifications based on the standard, and the China 2025 initiative has made a similar all-in commitment to OPC UA. We’ve made our own contributions to the world of OPC UA with new and updated products. Discrete manufacturing is also getting in on the interoperability act, with the German machine tool association VDW announcing the open universal machine tool interface (umati) initiative, which incorporates OPC UA into its architecture.

Looking ahead

The big lesson from all this energetic activity? IoT is a catalyst for digital transformation across traditional boundaries. We’re seeing new ecosystems and solutions emerge that unify data and insights from multiple places to enable new possibilities. As smart cities, vehicles, buildings, spaces, energy, and more converge, the opportunities grow—and so do needs for end-to-end manageability and security. We are committed to solving these challenges with built-in connectivity, real-time performance, and security innovation at the intelligent edge. Learn more about how Microsoft is helping build the connected future.

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4 innovations that are revolutionizing the Internet of Things

The Internet of Things (IoT) is reshaping every industry from manufacturing to medicine, and opportunities to transform business are nearly limitless. And while IoT is a complicated endeavor requiring multiple partners, skillsets, and technologies, new innovations are making projects easier to deploy, more secure, and more intelligent than ever.

Below I’ve called out four innovations that are revolutionizing the IoT industry. To learn more about how to take advantage of these innovations, be sure to register for our upcoming IoT in Action Virtual Bootcamp.

IoT in Action virtual event details

1. Artificial intelligence (AI) and cognitive capabilities

Cognitive services and AI used to come with a high price tag. But times have changed, and these capabilities are becoming increasingly accessible.

IoT Hub and Cognitive Services enable you to tailor IoT solutions with advanced intelligence without a team of data scientists. Not only do AI and Cognitive Services make it easier to infuse IoT solutions with capabilities such as image recognition, speech analytics, and intelligent recommendations, but they also help companies act on the data being gathered and realize the true value of IoT. Scenarios are virtually limitless. Companies like UBER are using visual identity verification to increase platform security, and Spektacom is making cricket better with its AI-infused sticker for cricket bats that can deliver insights around batting style.

2. Real-time analytics at the intelligent edge

You need data analytics to make your IoT solution complete, but all the data you need is not where you want it to be—it’s at the edge. One solution is to reproduce a cloud environment locally, but this can be costly and you may end up having to support two solutions, not one.

Now you can extend cloud intelligence and analytics to the edge. Azure IoT Edge optimizes performance between the edge and cloud, reducing latency, so you get real-time data. This secure solution enables edge devices to operate reliably even when they have intermittent cloud connectivity, while also ensuring that only the data you need gets sent to the cloud. And by combining data from the cloud and data from the edge, you get the best of both worlds.

3. More secure IoT devices

IoT security continues to evolve. Which means it’s never been easier to lock down your IoT solutions. At Microsoft, we continue to build uncompromising security into every product we make. We recently released Azure Sphere, which is an end-to-end solution for creating highly-secure, connected devices using a new class of microcontrollers (MCUs). Azure Sphere powers edge devices, combining three key components including Azure Sphere certified MCUs, Azure Sphere OS, and the Azure Sphere Security Service.

4. Provisioning IoT quickly at scale

Provisioning IoT manually is time-intensive and can quickly become a showstopper, especially when you’ve got hundreds, thousands, or even millions of devices to configure. Even if manual provisioning is possible now, building in the capability to quickly and securely provision future devices is critical.

Azure IoT Hub features a Device Provisioning Service (DPS) that enables remote provisioning without human intervention. Azure DPS provides the infrastructure needed to provision millions of devices in a secure and scalable way. DPS extends trust from the silicon to the cloud where it creates registries to enable managed identity services including location, mapping, aging, and retirement. It works in a variety of scenarios from automatic configuration based on solution-specific needs to load balancing across multiple hubs to connecting devices based on geo-location.

Register for the IoT in Action Virtual Bootcamp

To learn more about how you can take advantage of these innovations, be sure to register for an IoT in Action Virtual Bootcamp. Whether you are an engineer, software architect, or practice owner, this virtual bootcamp will give you a clear understanding of IoT from device to cloud and accelerate the development of an IoT solution for your business.

This event will help you get hands on with the latest in IoT devices and cloud services including secure MCUs, IoT OSes, and advanced application services. You will also receive trusted guidance and a singular ecosystem view, supporting you in the design of secure IoT solutions that add real-world business value and create exciting new customer experiences. Join us to establish a leadership position in the IoT ecosystem by creating new experiences and revenue streams while optimizing bottom-line performance.

Register for an IoT in Action Virtual Bootcamp in your time zone:

Interested in attending one of our in-person IoT in Action event? Register for a free event coming to a city near you.

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Fast, accurate, stable and tiny: Innovative algorithms breathe life into IoT devices

——Group of guys standing around talking

In the larger quest to make the Internet of Things (IoT) a reality for people everywhere, building devices that can be both ultrafunctional and beneficent isn’t a simple matter. Particularly in the arena of resource-constrained, real-time scenarios, the hurdles are significant. The challenges for devices that require quick responsiveness—say, smart implants that warn of impending epileptic seizures or smart spectacles providing navigation for low-vision people—are multifold. Small form factors and tiny microcontrollers mean that the training and prediction, via machine learning, that would make these devices smart and helpful must take place in the cloud, requiring significant amounts of data to be amassed and uploaded in real time. This introduces very real hurdles in areas such as connectivity, bandwidth, latency, power, and even privacy and security. For an individual prone to seizures, enjoying a swim in the community center pool, timing (latency) is everything, and the ability to leave the house for an entire day on a single charge (power) is survival itself. In the case of smart spectacles, constantly uploading video to the cloud, too, would soon cause bandwidth, latency, and power concerns and almost certainly introduce privacy issues.

The solution then would seem to lie in the area of making machine learning and prediction algorithms that currently reside in the cloud local to the devices themselves. And yet the hardware capacity of such devices is severely constrained, often relying on IoT endpoints having just 2 KB of RAM and 32 KB flash memory.

“We are trying to change the IoT paradigm fundamentally.” – Manik Varma, Principal Researcher, Microsoft Research India

The EdgeML team at Microsoft Research India has been examining this challenge from the point of view of machine learning and is building a library of ML algorithms—the EdgeML library—intended to have a range of both traditional ML algorithms, as well as deep learning algorithms, including the use of recurrent neural networks (RNNs) that could be used to build such devices and tackle some of these applications. RNNs are powerful deep learning models in how they make use of sequential information and incorporate context from previous inputs; just as humans don’t start thinking from scratch every second, RNNs are networks with loops in them that allow information to persist.

Squeezing RNN models and code into a few kilobytes could allow RNNs to be deployed on billions of IoT devices, potentially transforming many existing challenges for individuals and communities across myriad life scenarios. Downsizing the RNN also could significantly reduce the prediction time and energy consumption and make RNNs feasible for real-time applications such as wake-word detection, predictive maintenance, and human activity recognition.

The problem is that RNN training is inaccurate and unstable as the time interval over which the sensor signal is being analyzed increases. And in the types of resource-constrained and real-time applications that we’re talking about above, an additional concern is RNN model size and prediction time.

In FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network—being presented at the 32nd Conference on Neural Information Processing Systems (NeurIPS 2018) in Montreal, Canada—Aditya Kusupati, Prateek Jain, and Manik Varma of Microsoft Research India, along with Manish Singh of the Indian Institute of Technology Delhi and Kush Bhatia and Ashish Kumar of the University of California, Berkeley, introduce innovative new architectures for efficient RNN training and prediction on severely resource-constrained IoT devices too tiny to hold existing RNN models.

FastGRNN stands for Fast, Accurate, Stable and Tiny Gated Recurrent Neural Network algorithm, designed to address the twin RNN limitations of inaccurate training and inefficient prediction. It turns out that FastGRNN matches the accuracies and training times of state-of-the-art unitary and gated RNNs but has significantly lower prediction costs. Models range from 1 to 6 KB for real-world applications.

“We asked ourselves, how can we get machine learning to actually run on such severely resource-constrained microcontrollers and IoT devices,” recalled India’s EdgeML team member and Principal Researcher Manik Varma. “The traditional IoT paradigm has been that these devices have been too weak to do AI, so everyone thought that all the data had to be sent to the cloud and all the decision making would happen there. But, unfortunately, this traditional paradigm cannot address lots of critical scenarios where you need to make decisions on the device itself.”

The team set out to conquer the four challenge areas presented by localizing machine learning on the microcontroller itself: bandwidth, latency, power, and privacy/security.

They had started this project roughly two years ago and turned heads at ICML 2017 when they published two papers (Bonsai and ProtoNN) showing how they had managed to deploy traditional machine learning on the world’s tiniest devices—microcontrollers smaller than a grain of rice, such as the ARM Cortex M0 with just 2 KB of RAM, and miniscule IoT boards, such as the Arduino Pro Mini, based on an 8-bit Atmel ATmega328P microcontroller operating at 8 MHz without any floating point support in hardware, with 2 KB RAM and 32 KB read-only flash memory.

It may have been the first time anyone in the world had gone so small with machine learning—and it got some serious attention.

“We are tackling critical scenarios beyond the pale of the traditional IoT paradigm, where it is not feasible to transmit sensor data to the cloud due to latency, bandwidth, energy, privacy, or security concerns and where the decision making needs to happen locally on the IoT edge or endpoint device itself.” – Manik Varma

Intent on building upon the success, the team intensified its focus on the more challenging problem of deep learning. In an IoT world, almost everything happening takes the form of a time series. Think of the case of a moisture sensor embedded in the soil on a farm taking periodic readings on water moisture at a specific location; based on a series of chronological readings, it would make a decision on whether to irrigate that particular location. The state of the art for analyzing time series is RNNs. And so, they started looking at leading RNNs as a way of solving the size and resource problem.

Honest, Abe – they’re tiny! One of the chips on which the EdgeML team is deploying its ML algorithms, sitting atop a Lincoln penny.

But RNNs have a couple of issues. One is that they are not very easy to train. Most RNNs and other deep learning methods are trained based on gradient descent¬–type algorithms. Unfortunately, in the case of RNNs, the gradients are not very stable. They explode in some directions (to infinity) and vanish (to zero) in others. This has been a problem for RNNs since the time they were developed. Researchers have come up with many ways to solve this problem. One is unitary RNNs, which restrict the range of the state transition matrix’s singular values. Unfortunately, they also increase the model size, as they require a larger number of hidden units to make up for the loss in expressive power. Therefore, unitary RNNs are not ideal for these tiny devices, where you want to conserve memory and make predictions as quickly as possible.

Gated RNNs, another idea that researchers have experimented with to address this issue, stabilize training by adding extra parameters. Gated RNNs can deliver state-of-the-art prediction accuracies, but the models themselves are sometimes even larger than unitary RNNs.

The EdgeML Team came up with another approach.

“What we realized is, if you take the standard RNN architecture and just add a simple residual connection, it stabilizes the RNN training and it does so provably,” said Varma. “It only has two extra scalar parameters—as compared to an RNN—and it gets you better accuracy than any of the unitary methods proposed so far.”

Based on this insight, they then modified the residual connection slightly by converting it to a gate. “This achieved an accuracy that matches the state of the art in LSTMs, GRUs, and so on, but with a model that is two to four times smaller,” explained Varma. Gated RNN that hit speed, achieved accuracy, remained stable and – was tiny. FastGRNN.

To compress this model even further, the researchers then took all the FastGRNN matrices and made them low rank, sparse, and quantized. This reduced the size by a factor of 10.

“Based on this, we were able to build a wake-word detector for Cortana using a 1KB model and fit it on the Arduino boards,” said Varma.

The team’s code is available online for free on Github.

Accommodating real world IoT off the cloud

The real-life applications brought into the realm of the possible by FastGRNN are seemingly unlimited, with ideas cropping up across smart health care, precision agriculture, augmenting of abilities for people with special needs, and even space exploration. The EdgeML team is prototyping a smart cane for low-vision people.

“We’re focusing on getting the machine learning algorithms as compact as possible. Our hope is that if you can fit them onto the tiniest microcontroller, then any other microcontroller can also run them,” said Senior Researcher and Edge ML teammate Prateek Jain.

Hence the EdgeML team’s smart cane prototype that can interpret gestures and then can interact with the user’s phone. A twirl with the cane gets the user’s phone to report present location. A double-swipe gets the cane to answer the owner’s phone. A fall detector, for example, for the blind or for the elderly could instruct the owner’s phone to call for help.

Smart spectacles for people with low-vision represent another example of on-the-spot, real-time training and prediction that could transform lives and one deeply significant to Varma, who is himself low-vision. “It would be enormously helpful to have a camera on my glasses that would tell me what’s happening in the world, who I am looking at, and so on, he said. “You can’t send the whole video stream to the cloud; it would be too costly and there wouldn’t be enough bandwidth.” And again, latency is an issue if the spectacles were to be depended upon to warn one of hazards when walking on the street.”

Privacy is paramount and a problem that is addressed by miniaturizing deep learning. “You don’t want your visual or voice data being streamed to the cloud all the time. That would be creepy, everything you say or see in your home being recorded and sent to the public cloud,” said Varma. With the EdgeML team’s methodology, voice detection is run locally and not being sent to the cloud at all.

The EdgeML team (left to right) – Aditya Kusupati, Don Dennis, Manik Varma, Harsha Vardhan Simhadri, Shishir Patil, Rahul Sharma, Nagarajan Natarajan, Prateek Jain.

“We spent a lot of time talking to many different Microsoft product groups, startups, scientists, and the government trying to figure out applications,” recalled Jain.

An interesting application the team came across was in astronomy and space exploration. Resource scarcity—specifically energy—in spacecraft and machines that are sent into deep space is a huge issue. Another is the fact that satellites and probes collect an enormous amount of data via telescopes, cameras, and other sophisticated sensors; yet astonishingly, only a miniscule fraction of the data that is sensed is ever seen by a human being. If there were energy-efficient, low-latency machine learning available on the sensors themselves, the on-chip algorithms could learn what data is most interesting, and then determine which data would be sent for human analysis.

Varma has been invited as a Visiting Miller Research Professor at UC Berkeley to work on some of these problems. “It’s one of the great things about Microsoft Research, the amount of freedom and support you get for blue skies research, to take risks and to collaborate with people inside and outside Microsoft,” he smiled. In the case of FastGRNN, we may be looking at the stars.

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Sam George: What to expect from Microsoft at this week’s IoT Solutions World Congress

It’s amazing to see how IoT is transforming our customers’ businesses—from optimizing operations and reducing unplanned downtime with companies like Chevron, to powering new connected vehicle experiences as we recently announced with Volkswagen.

Beyond business transformation, IoT has the potential to create more efficient and vibrant cities and communities by providing new insights and approaches to transportation and traffic, energy reduction, construction, utilities, parking, and so much more.

We are continuing to simplify the customer journey for secure, scalable IoT solutions for the cloud and the edge with a large set of announcements last month, including the general availability of Azure IoT Central at our Ignite 2018 conference, and more just last week about bringing intelligence to the edge in Windows IoT.

This week at IoT Solutions World Congress, we look forward to connecting with companies across industries and inspiring them with new possibilities for IoT, from creating Digital Twins of physical environments to taking advantage of Vision and AI on edge devices. We’ll also be talking about how we’re breaking down common barriers to entry in IoT by addressing security from the start with solutions like Azure Sphere and Azure Security Center for IoT, and empowering organizations to provision and customize fully managed IoT solutions in minutes with Azure IoT Central. And that’s just the start.

Vision and AI at the edge power breakthrough applications

Vision and AI capabilities on edge devices are the ultimate sensor and will help companies create breakthrough applications. From automatically detecting manufacturing defects, to detecting any object, to detecting unsafe conditions in the enterprise or industry—the possibilities are endless.

Today we are announcing the public preview of a Vision AI developer kit, the newest addition in the Microsoft Azure IoT starter kit family, for IoT solution makers to easily deploy AI models built using Azure Machine Learning and Azure IoT Edge. The kit includes a device using Qualcomm Visual Intelligence Platform for hardware acceleration of the AI model to deliver superior inferencing performance. To get started, visit www.visionaidevkit.com.

Vision AI developer kit

Model the physical world with Azure Digital Twins

At Ignite, we introduced Azure Digital Twins, a breakthrough new offering in our IoT platform that represents the evolution of IoT. Azure Digital Twins enables customers and partners to create a digital model of any physical environment, connect it to IoT devices using Azure IoT Hub to make the model live, and then respond to changes in it to create serverless business logic. Customers and partners can now query Azure Digital Twins in the context of a space—rather than from separate sensors—empowering them to build repeatable, scalable experiences that correlate data from digital sources and the physical world.

Today we are announcing that Azure Digital Twins is available in public preview. Several of our early partners are at IoT Solutions World Congress showcasing their solutions that span a wide range of applications that represents the broad applicability of Azure Digital Twins, including:

IoT partners

Applied innovation for smarter cities

Today, as cities and communities embrace digital transformation, technology like Digital Twins and easy-to-use machine learning is helping ideas become real, actionable solutions. Environments and infrastructure of all types—offices, schools, hospitals, banks, stadiums, warehouses, factories, parking lots, streets, intersections, parks, plazas, electrical grids, and more—can become smarter to help the people who use them live better lives. We’ll have more to share on this topic at Smart City Expo World Congress in November.

Connect with us at IoT Solutions World Congress

If you’re in Barcelona this week, connect with us at the Microsoft IoT booth (# C321) and hear from us in the following sessions: