Power Down in Azure Sphere enables power-constrained scenarios for IoT devices to provide more flexibility and options for power management when building and deploying Azure Sphere devices.

Tyler Fox, PM in the Azure Sphere OS team, demos Power Down and talks through low-power IoT device scenarios and how Azure Sphere maintains device security and connectivity even in ultra-low power scenarios.

Here’s a great session on Azure RTOS

Azure RTOS is a small, fast, reliable, and easy-to-use real-time operating system. In this video introduction, we’ll discuss the major components that make up the Azure RTOS ecosystem: the ThreadX RTOS, NetX TCP/IP stack, FileX embedded file system, GUIX embedded GUI, and USBX embedded USB stack. We’ll also cover some tools to make development easier, such as GUIX Studio (a WYSIWYG GUI designer that auto-generates C code to run on embedded devices) and TraceX (an event trace tool that feels like a software logic analyzer).

Guest Speaker: Scott Larson – Azure IoT Senior Engineer
Deep Dive Host: Pamela Cortez – Azure IoT

Cognizant’s Connected Factories is a next-generation offering that accelerates solution development and deployment for Industry 4.0 solutions helping manufacturers improve productivity, yield and safety.

It shortens time to value with pre-defined information meta models as well as configurable microservices for industry standard KPIs; fully leveraging the latest of Azure IoT services stack.

Learn more about Cognizant’s Connected Factories solution: https://aka.ms/iotshow/cognizant

In this video, walk through the steps for creating and visualizing indoor maps, querying map data and integrating it with IoT.

The Azure Maps Creator service enables customers to upload their private maps, floorplans, spaces and asset information to manage, monitor, and track their IoT assets within spaces like offices, malls, and airports, with extensibility to support other private map scenarios considered private in nature all within a customer’s control. 

Tiny Machine Learning (TinyML) is the latest embedded software technology that moves hardware into that almost magical realm, where machines can automatically learn and grow through use, like a primitive human brain.

Until now building machine learning (ML) algorithms for hardware meant complex mathematical modes based on sample data, known as “training data,” in order to make predictions or decisions without being explicitly programmed to do so. And if this sounds complex and expensive to build, it is. On top of that, traditionally ML-related tasks were translated to the cloud, creating latency, consuming scarce power and putting machines at the mercy of connection speeds. Combined, these constraints made computing at the edge slower, more expensive and less predictable.

Speaking of NVIDIA, Microsoft Developer takes a look at the latest device in the NVIDIA Jetson line of GPU-accelerated IoT devices, the Jetson Xavier NX.

A device which brings supercomputer-class performance to Edge applications in an ultra-compact form-factor.

To demonstrate this, we configure the device with Azure IoT Edge and deploy the NVIDIA DeepStream SDK Module from the Azure Marketplace to produce object detection telemetry with Azure Stream Analytics then push those results into Time Series Insights and Power BI.

Come see how the pairing of NVIDIA devices and Azure IoT Services make for a first-class solution of AI at the Edge!

Learn more about NVIDIA DeepStream on IoT Edge: https://aka.ms/iotshow/NVIDIADeepStream

Are you a developer implementing, coding or maintaining cloud or edge components of IoT solutions?

Is part of your job to manage devices life cycle – set up, configuration, and maintenance – using cloud services?

Do you design IoT solutions including device topology, connectivity, debugging, and security?

Do you implement solutions to manage, monitor, and transform data related to IoT?

If these job responsibilities sound familiar, I have a great opportunity for you to showcase your skills and be recognized for them: Take AZ-220 exam: Microsoft Azure IoT Developer.

Hear more about the new Microsoft Certified: Azure IoT Developer Specialty and resources to learn how to build IoT solutions with Azure IoT. Visit http://aka.ms/azureiotdeveloper to learn more about the Azure IoT Developer Specialty.

Resources

The combination of 5G and edge computing promises to fast-track the use of artificial intelligence (AI) in the Internet of Things (IoT).

With 10 to 20 times faster speeds and dramatically lower latency, 5G makes it much more feasible to process AI workloads locally at the edge.

Hardware is about to get interesting again.

This speed and reduced latency is essential to an array of IoT applications such as smart cities, transportation, intelligent manufacturing, e-health, smart farming, and so on. This is why Gartner predicts that 75 percent of enterprise-generated data will be processed outside a traditional data center or cloud by 2022, compared with 10 percent today.