Updates to Microsoft's Azure IoT Edge Offer Greater AI and Edge Solutions
Microsoft is hitting the IoT angles hard. Take a look at what Azure IoT Edge is now offering and how AI is slowly being integrated into edge networks.
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Last week heralded a significant update but Microsoft in Azure IoT Edge, their cloud solution for IoT. It’s emerging from preview mode and gaining support for new hardware devices, management services, and developer tools. The service "delivers cloud intelligence locally by deploying and running artificial intelligence (AI), Azure services, and custom logic directly on cross-platform IoT devices," according to the Azure website.
Microsoft detailed some of the use cases that had been realized in their preview stage:
"Since we introduced Azure IoT Edge just over a year ago, we have seen many examples of the real-world impact from the factory floor to the farm to run cloud intelligence directly on IoT devices. Now devices can act immediately on real-time data—whether it be recognizing a crack in a pipe from an aerial view or predicting equipment failure before it happens. As we evolve toward a world of ubiquitous computing, the design of the IoT solution spanning hardware, edge, and cloud must be consistent and secure to drive real impact."
IoT Edge is now open source and available on Github, which Microsoft recently acquired for $7.5 billion. The new offering also provides a great framework for developing and deploying custom IoT edge modules.
IoT Edge is made up of three components:
- Azure IoT Edge modules are containers that run Azure services, 3rd party services, or your own code. They are deployed to IoT Edge devices and execute locally on those devices.
- The Azure IoT Edge runtime runs on each IoT Edge device and manages the modules deployed to each device. An interesting fact is this runtime will be open sourced to the developer community so that they can make changes and additions to it.
- A cloud-based interface enables you to remotely monitor and manage IoT Edge devices.
Increased Functionality to IoT and the Edge
What's truly interesting about Microsoft's developments is the capabilities it awards in developing edge computing solutions that were previously cost and time prohibitive, consistent with a move towards a hybrid cloud/edge computing model with greater analytic capabilities due to AI and machine learning.
AI and machine learning can be used to make a factory truly smart: for example, enabling an asset or piece of equipment to not simply monitor a machine but make decisions about what’s going on in the factory floor without the need of human intervention. The combination of Sensors and AI can enable a machine to gain insight into a failing part before it fails and alert workers to instigate predictive maintenance rather than simply running on an automated repair schedule. In some instances, the machine may even be able to self-repair. This is light years away from an earlier IoT era of machines simply collecting a deluge of data without the real ability to analyze data effectively or efficiently leading to either large amounts of unanalyzed data, or sole reliance on cloud computing causing significant delays in data processing and decision making in time critical applications.
I was interested to get some perspective from an end user about the impact of the IoT Azure improvements on their business and spoke to Huck Bales, Senior MES Engineer at Stone Technologies;
"Azure IOT Edge is truly disruptive because it provides a framework for IIOT design patterns. I can develop a collection of containers in a modular way, each providing a specific function, and deploy the required functionality to the edge.
From a market perspective, this enables large companies with many factories to deploy a low-cost and consistent gateway for process and production data.
Perhaps more interesting is the opportunity for small manufacturers that may have only a PLC and a panel view. Now they have an affordable way to get that data directly to the cloud to visualize their process."
Azure IoT Edge will include a simplified developer experience. The service will support more programming languages than other edge offerings on the market, including C#, C, Node.js, Python, and Java, so developers have more choice in how they program edge modules. The service will also aim to simplify module development by coding, testing, debugging, and deploying from VSCode. And CI/CD pipelines with VSTS will help developers manage the complete lifecycle of the Azure IoT modules from development, testing, staging, and deployment.
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