Category Archives : Internet of Things

20

Jun

Location and Maps in Azure IoT Central powered by Azure Maps

Azure IoT Central brings the simplicity of SaaS for IoT with built-in support for IoT best practices and world class security and scalability with no cloud expertise required. We have been constantly adding features and true to the promise of SaaS applications, you can just start using new features right away to build production-grade applications without worrying about managing infrastructure.

This blog post is part of a series of blog posts you will start seeing for new features in Azure IoT Central in the upcoming weeks.

Azure IoT Central now leverages Azure Maps. A portfolio of geospatial functionalities natively integrated into Azure to enable users with fresh mapping data necessary to provide geographic context to their location aware IoT applications. We received several interests from public preview customers to leverage geospatial services for various use cases ranging from simply localizing their devices, validating location information, spatially referencing device locations on a map, to geofencing use cases around their devices. As any other property in Azure IoT Central, location metadata can be persisted on the cloud and updated either by the device itself (device properties) or the user (application properties). By integrating with Azure Maps, user can now give geographic context

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20

Jun

Location and Maps in Azure IoT Central powered by Azure Maps

Azure IoT Central brings the simplicity of SaaS for IoT with built-in support for IoT best practices and world class security and scalability with no cloud expertise required. We have been constantly adding features and true to the promise of SaaS applications, you can just start using new features right away to build production-grade applications without worrying about managing infrastructure.

This blog post is part of a series of blog posts you will start seeing for new features in Azure IoT Central in the upcoming weeks.

Azure IoT Central now leverages Azure Maps. A portfolio of geospatial functionalities natively integrated into Azure to enable users with fresh mapping data necessary to provide geographic context to their location aware IoT applications. We received several interests from public preview customers to leverage geospatial services for various use cases ranging from simply localizing their devices, validating location information, spatially referencing device locations on a map, to geofencing use cases around their devices. As any other property in Azure IoT Central, location metadata can be persisted on the cloud and updated either by the device itself (device properties) or the user (application properties). By integrating with Azure Maps, user can now give geographic context

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19

Jun

Enabling Smart Manufacturing with Edge Computing

Smart Manufacturing envisions a future where factory equipment can make autonomous decisions based on what’s happening on the factory floor. Businesses can more easily integrate all steps of the manufacturing process including design, manufacturing, supply chain and operation. This facilitates greater flexibility and reactivity when participating in competitive markets. Enabling this vision requires a combination of related technologies such as IoT, AI/machine learning, and Edge Computing. In this article, we will introduce Edge Computing and discuss its role in enabling Smart Manufacturing.

What is Edge Computing?

Put simply, Edge Computing is about taking code that runs in the cloud and running it on local devices or close to it. Like in a gateway device or a PC sitting next to the device.

To understand Edge Computing it helps to think of an IoT solution as generally having three components:

Things like IoT devices, which generate sensor data. Insights you extract from this data. Actions you perform based on these insights to deliver some sort of value.

With Edge Computing, you move the insights and actions components from the cloud to the device. In other words, you bring some of the code used to process and extract insights from the data,

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07

Jun

Using STMicroelectronics starter kits to connect to Azure IoT in minutes

Microsoft partners with silicon vendors such as STMicroelectronics to simplify and accelerate the development of embedded systems, so our customers can move projects from proof of concepts to production faster. One of the most common issues in IoT project development is the passage from proof of concept to production, from a handful of devices to deployment and management of devices at an IoT scale and from development hardware to mass produced silicon.

STMicroelectronics offers a wide range of IoT hardware along with pre-integrated software, a powerful development ecosystem and valuable starter kits. With these, connecting to Azure IoT Hub the cloud platform, monitor, and manage billions of IoT assets using one of the Microsoft Azure Certified ST devices takes minutes and you don’t have to write any code! This magic is possible because of the integration ST provides under the cover. For example, STM32 IoT Discovery Kit Node is an Arm® Cortex®-M4-core-based developer kit and sporting a full set of low power wireless connectivity options and environmental, motion and ranging sensors. FP-CLD-AZURE1 is an STM32Cube function pack that ST developed for this kit. Azure IoT C SDK is integrated into the middleware of this function pack, which enables direct and

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05

Jun

Use Azure Data Lake Analytics to query AVRO data from IoT Hub

Recently a customer asked me how to read blob data produced from the routing capability of Azure IoT Hub. To provide this customer with a complete answer, I put together a step-by-step guide that I am happy to share with you in the video below.

One of the common patterns of Internet of Things applications is called “cold path” and consists of storing all data produced by IoT devices in the cloud for later processing. To make such an implementation trivial, Azure IoT Hub supports routing of messages coming from devices directly to cloud storage services. IoT Hub can also apply simple rules based on both properties, and the message body can route messages to various custom endpoints of your choice. IoT Hub will write blob content in AVRO format, which has both message body and message properties. Great for data/message preservation, AVRO can be challenging for querying and processing the data. Here is a suggested solution to process this data.

Many of the big data patterns can be used for processing non-relational data files in custom file formats. Focusing on cost and deployment simplicity, Azure Data Lake Analytics (ADLA) is one of the only “pay per query” big data

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04

Jun

Regenerative Maps alive on the Edge

This week Mapbox announced it will integrate its Vision SDK with the Microsoft Azure IoT platform, enabling developers to build innovative applications and solutions for smart cities, the automotive industry, public safety, and more. This is an important moment in the evolution of map creation. The Mapbox Vision SDK provides artificial intelligence (AI) capabilities for identifying objects through semantic segmentation – a technique of machine learning using computer vision that classifies what things are through a camera lens. Semantic segmentation on the edge for maps means objects such as stop signs, crosswalks, speed limits signs, people, bicycles, and other moving objects can be identified at run time through a camera running AI under the covers. These classifications are largely referred to as HD (high definition) maps.

HD maps are more machine friendly as an input to autonomous vehicles. Once the HD map objects are classified, and because other sensors like GPS and accelerometer are onboard, the location of these objects can be registered and placed onto a map, or in the advancement of “living maps,” registered into the map at run time. This is an important concept and where edge computing intersects with location to streamline the digitization of our

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30

May

Digging in with Azure IoT: Our interactive developer guide

The Internet of Things (IoT) presents many compelling opportunities for developers With the right tools and guidance, it doesn’t need to be intimidating. The conceptual and technical differences between IoT and traditional web and application are relatively easy to grasp. Plus, Microsoft offers a full range of managed services to make it even easier, while enabling you to experiment and scale. If your main skillset is in the Microsoft ecosystem, you can jump right in with Visual Studio Code, .NET, and Azure. If you prefer other languages and tools, our open-source SDKs will enable you to work with Azure solutions while staying in your comfort zone. Either way, you can get started quickly with our Azure IoT developer guide that will take you through common application patterns and tutorials that will have you up and running fast.

The IoT Application pattern

When it comes to knowing where to start, it can help to have a conceptual framework that organizes services and technologies in a logical way. We tend to think of IoT architecture as being divided into three main categories, each of which has considerations distinct from traditional development architectures:

Things: The devices and sensors in the field that are

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18

May

Azure the cloud for all – highlights from Microsoft BUILD 2018

Last week, the Microsoft Build conference brought developers lots of innovation and was action packed with in-depth sessions. During the event, my discussions in the halls ranged from containers to dev tools, IoT to Azure Cosmos DB, and of course, AI. The pace of innovation available to developers is amazing. And, in case there was simply too much for you to digest, I wanted to pull together some key highlights and top sessions to watch, starting with a great video playlist with highlights from the keynotes.

Empowering developers through the best tools

Build is for devs, and all innovation in our industry starts with code! So, let’s start with dev tools. Day one of Build marked the introduction of .NET Core 2.1 release candidate. .NET Core 2.1 improves on previous releases with performance gains and many new features. Check out all the details in the release blog and this great session from Build showing what you can use today:

.NET Overview & Roadmap: In this session, Scott Hanselman and Scott Hunter talked about all things .NET, including new .NET Core 2.1 features made available at Build.

Scott Hanselman and Scott Hunter sharing new .NET Core 2.1.

With AI being top

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14

May

Using the Azure IoT Python SDK: make sure you check the version!

Since the release in 2016, developers are using our Azure IoT Python SDK to write device and back-end applications to connect to Azure IoT Hub and Device Provisioning Service, as well as writing modules for Azure IoT Edge (preview). Python is a popular choice for prototyping, and it is gaining traction in the embedded world.

If you decide to use the Python SDK for development, there are few things you should keep in mind: Python SDK is a wrapper on top of our Azure IoT C SDK, and we release binary packages on pip for Windows, Ubuntu, and Raspbian, all of which are compatible with Python 2 and Python 3. This approach has its ups and downs. On the upside, the features you see in C are available in Python with no functionality difference. On the downside, it is not a native Python SDK. Application Programming Interfaces (APIs) that we exposed may look different from typical Python APIs; and as a developer, you will need to pay attention the architecture of underlying platform, especially when you are using pip!

At a high level, there are three things that must align to reference the Python SDK properly: Python version (2 or

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07

May

What’s new with Azure IoT Edge?

At Microsoft Build 2017 we shared our vision for Azure IoT Edge. At that time we demonstrated the idea of what Azure IoT Edge could do with Azure Stream Analytics job and Azure Machine Learning workloads by moving from Azure cloud to an IoT Edge device so that decisions could be made quickly and reliably without having to rely on the public Internet. This allowed million-dollar machines to operate reliably and safely with Azure IoT Edge, making intelligent decisions based on data from the machine. Deployment of these workloads can now be at a scale of thousands or millions of devices.

In November 2017, we shipped the public preview of Azure IoT Edge with the ability to move workloads from the Azure to Edge devices. These workloads included the AI Toolkit for Azure IoT Edge, Azure Machine Learning, Azure Stream Analytics, Azure Functions, and your own code. With these services on the edge, you could build rich and intelligent applications which operate locally, but can easily be deployed and managed from the Azure IoT Hub. We also articulated the security model for Azure IoT Edge and announced partnerships with NXP and Microchip for support of this model.

Since the public

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