This blog post is co-authored by Emmanuel Bertrand, Senior Program Manager, Azure IoT.
We recently announced Azure Cognitive Services in containers for Computer Vision, Face, Text Analytics, and Language Understanding. You can read more about Azure Cognitive Services containers in this blog, “Brining AI to the edge.”
Today, we are happy to announce the support for running Azure Cognitive Services containers for Text Analytics and Language Understanding containers on edge devices with Azure IoT Edge. This means that all your workloads can be run locally where your data is being generated while keeping the simplicity of the cloud to manage them remotely, securely and at scale.
Whether you don’t have a reliable internet connection, or want to save on bandwidth cost, have super low latency requirements, or are dealing with sensitive data that needs to be analyzed on-site, Azure IoT Edge with the Cognitive Services containers gives you consistency with the cloud. This allows you to run your analysis on-site and a single pane of glass to operate all your sites.
These container images are directly available to try as IoT Edge modules on the Azure Marketplace:
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It’s amazing to look back at everything we’ve learned from our customers since we first released HoloLens. Across manufacturing, education, retail, gaming, and many other industries, developers and businesses are using mixed reality in their daily workflows and giving us feedback on what they’d like to see next. When we look across all the mixed reality solutions that customers have been building over the last few years, two things really stand out: collaboration and spatial awareness. Customers want to easily share their mixed reality experiences and place applications in the context of the real world, and thereby increase their efficiency and achieve greater productivity.
Yesterday at MWC Barcelona, we announced Azure Spatial Anchors, a mixed reality service that enables you to build a new generation of mixed reality applications that are collaborative, cross-platform, and spatially aware. Today, we’re sharing two application patterns gaining momentum across industries, and how Azure Spatial Anchors can help you deliver them with greater ease and speed.
Collaborative mixed reality experiences
Mixed reality enables us, as humans, to do more and to collaborate with those around us in a more natural and intuitive way. Whether it’s architects and site workers reviewing the day’s plans for a
The Internet of Things (IoT) has expanded the world of computing far beyond mobile and PC, bringing a new and ever-growing class of cloud-connected devices that is on track to reach 20 billion devices by 2020. This year’s Mobile World Congress (MWC) programming reflects this profound shift, where IoT is transforming industries from agriculture to retail, leveraging emerging technologies including AI, Mixed Reality, edge computing, 5G, and more to not only accelerate business but to also address societal issues like improving our global food supply, reducing energy use, and waste.
IoT unlocks the power of the intelligent cloud and intelligent edge, enabling businesses to take informed actions based on real-time insights from any physical part of their business. Customers including Chevron, Volkswagen, Kohler, CBRE, Thyssenkrupp, and more are embracing IoT as critical to their technology portfolio and using it to optimize business processes, create new connected experiences, and manage digital and physical assets at scale.
Today, Microsoft made a series of announcements for new devices and cloud services that will further increase the strategic value of IoT. Microsoft boasts one of the fastest growing IoT partner ecosystems in the market, with 10,000 IoT partners developing intelligent edge to intelligent cloud
The Internet of Things (IoT) is becoming mainstream. Companies are seeing market-making benefits from IoT and deploying at scale – from transforming operations and logistics, remote monitoring, and predictive maintenance at the edge to new consumer experiences powered by connected devices. In all of these solutions, IoT data and AI are producing powerful insights that lead to new opportunities.
Today at MWC 2019, we’re announcing that Microsoft and SAP are extending our partnership to IoT. 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.
Microsoft has collaborated with SAP for over two decades to enable enterprise SAP solution deployments which include Azure, Windows Server, and SQL Server. Microsoft and SAP have also collaborated in the Industrial Internet Consortium, the OPC Foundation, and the Plattform Industrie 4.0 for many years, jointly helping to define and build products on open industrial interoperability and security standards. Last fall, we also announced the Open Data Initiative with SAP and Adobe, designed to eliminate data silos and deliver world-class customer experiences.
Now SAP and Microsoft are expanding their partnership
As the Internet of Things (IoT) disrupts global business across every industry, opportunities abound. Partners are building on Microsoft IoT innovations and expanding solution accelerators, while customers of every size are reaping the rewards through increased productivity and efficiency, new revenue streams, and broader market share.
Read on to discover how Microsoft and our partners are making IoT faster, easier, and more cost effective through innovations in Windows IoT, Azure IoT, and Azure Sphere. For greater depth and inspiration, as well as some fantastic networking opportunities, be sure to attend the IoT in Action global event in Nuremberg on February 25, 2019.
New innovations in Azure IoT Greater compatibility and flexibility
Azure IoT is evolving to make it more compatible with a growing list of technologies, offering far greater choice and flexibility. In 2018, Microsoft announced the general availability of Azure IoT Edge. And as of February, Azure IoT Edge is now able to run on virtual machines (VM) using a supported operating system. Also announced in February: Azure IoT Hub Java SDK will now support the Android Things platform.
Further integration with artificial intelligence and machine learning
Microsoft partners and customers are driving remarkable innovation through integration
Most IoT solutions, including our Azure IoT reference architecture, use several different services. An IoT message, starting from the device, could flow through a dozen or more services before it is stored or visualized. If something goes wrong in this flow, it can be very challenging to pinpoint the issue. How do you know where the message is dropped? For example, you have an IoT solution that uses five different Azure services and 1,500 active devices. Each device sends ten device-to-cloud messages/second (for a total of 15,000 messages/second), but you notice that your web app sees only 10,000 messages/second. Where is the issue? How do you find the culprit?
To completely understand the flow of messages through IoT Hub, you must trace each message’s path using unique identifiers. This process is called distributed tracing. Today, we’re announcing distributed tracing support for IoT Hub, in public preview.
Get started with distributed tracing support for IoT Hub
With this feature, you can:
Precisely monitor the flow of each message through IoT Hub using trace context. This trace context includes correlation IDs that allow you to correlate events from one component with events from another component. It can be applied for a
Microsoft IoT Show, the place to go to hear about the latest announcements, tech talks, and technical demos, is starting a new interactive, live-streaming event and technical video series called IoT Deep Dive!
Each IoT Deep Dive will bring in a set of IoT experts, like Joseph Biron, PTC CTO of IoT, and Chafia Aouissi, Azure IoT Senior Program Manager, during the first IoT Deep Dive, “Building End to End industrial Solutions with PTC ThingWorx and Azure IoT.” Join us on February 20, 2019 from 9:00 AM – 9:45 AM Pacific Standard Time to walk-through end to end IoT solutions, technical demos, and best practices.
Come learn and ask questions about how to build IoT solutions and deep dive into intelligent edge, tooling, DevOps, security, asset tracking, and other top requested technical deep dives. Perfect for developers, architects, or anyone who is ready to accelerate going from proof of concept to production, or needs best practices tips while building their solutions.
PTC ThingWorx and Microsoft Azure IoT are proven industrial innovation solutions with a market-leading IoT cloud infrastructure. Sitting on top of
Built-in machine learning (ML) models for anomaly detection in Azure Stream Analytics significantly reduces the complexity and costs associated with building and training machine learning models. This feature is now available for public preview worldwide.
What is Azure Stream Analytics?
Azure Stream Analytics is a fully managed serverless PaaS offering on Azure that enables customers to analyze and process fast moving streams of data, and deliver real-time insights for mission critical scenarios. Developers can use a simple SQL language (extensible to include custom code) to author and deploy powerful analytics processing logic that can scale-up and scale-out to deliver insights with milli-second latencies.
Traditional way to incorporate anomaly detection capabilities in stream processing
Many customers use Azure Stream Analytics to continuously monitor massive amounts of fast-moving streams of data in order to detect issues that do not conform to expected patterns and prevent catastrophic losses. This in essence is anomaly detection.
For anomaly detection, customers traditionally relied on either sub-optimal methods of hard coding control limits in their queries, or used custom machine learning models. Development of custom learning models not only requires time, but also high levels of data science expertise along with nuanced data pipeline engineering skills. Such
Azure IoT Edge is a fully managed service that allows you to deploy Azure and third-party services—edge modules—to run directly on IoT devices, whether they are cloud-connected or offline. These edge modules are container-based and offer functionality ranging from connectivity to analytics to storage—allowing you to deploy modules entirely from the Azure portal without writing any code. You can browse existing edge modules in the Azure Marketplace.
Today, we’re excited to offer the open-source Azure IoT Edge runtime preinstalled on Ubuntu virtual machines to make it even easier to get started, simulate an edge device, and scale out your automated testing.
Why use virtual machines?
Azure IoT Edge deployments are built to scale so that you can deploy globally to any number of devices and simulate the workload with virtual devices which is an important step to verify if your solution is ready for mass deployment. The easiest way to do this is by creating simulated devices with Azure virtual machines (VMs) running the Azure IoT Edge runtime to scale your testing from the earliest stages of development—even before you have production hardware.
Azure VMs are:
• Scalable/automatable: deploy as many as you need
• Persistent: cloud- managed, rather than
Connectivity is often the first challenge in the Internet of Things (IoT) world, that’s why more than three years ago we released Azure IoT SDKs. Azure IoT SDKs enable developers to build IoT applications that interact with IoT Hub and the IoT Hub Device Provisioning Service. The SDKs cover most popular languages in IoT development, including C, .NET, Java, Python, and Node.js, as well as popular platforms like Windows, Linux, OSX, and MBED. Since April 2018, we have added official support for iOS and Android to enable mobile IoT scenarios.
Today, we are happy to share that Azure IoT Hub Java SDK will officially support the Android Things platform. This announcement showcases our commitment to enable greater choice and flexibility in IoT deployments. Developers can leverage the benefits of the Android Things operating system on the device side, while using Azure IoT Hub as the central message hub that scales to millions of simultaneously connected devices.
All features in the Java SDK will be available on the Android Things platform, including Azure IoT Hub features we support and SDK-specific features such as retry policy for network reliability. In addition, the Android Things platform will be tested with every release. Our