Windows 10 and the ‘edge’

October 13th, 2018 by Stephen Jones Leave a reply »

Microsoft recently announced in ablog post. “Windows 10 IoT delivers innovation and intelligence at the edge with the October 2018 Update” The Windows 10 October 2018 update will deliver ‘edge’ intelligence with machine learning, industrial strength security, new silicon options, and additional monetization models for distributors and sellers for enterprise Internet of Things (IoT) projects.

The edge” is a theoretical space where a data center resource may be accessed in the minimum amount of time. The edge, in simple terms, is where you generate, collect, and analyze data i.e. where the data is generate. Edge computing technology is applied to smartphones, tablets, sensor-generated input, robotics, automated machines on manufacturing floors, and distributed analytics servers that are used for “on the spot” computing and analytics.

Traditional datacenter architecture is all about central computing powerhouses, from where information is sent and received across globally spread networks. Here, the larger the distance between the endpoint and the datacenter, the higher the response time. In many applications, this incrementally larger time gap is inconsequential. However, in many others, it’s critical. For example:
• when the computation required for rendering the content is carried out close enough to AR and VR devices.
• Autonomous vehicles require near real-time feedback from external networks to make course corrections and avoid collisions
• In IoT, many analytical actions need to be carried out closed to the devices that generate the source data.
• HD video content, if cached closer to large concentrations of people who’re likely to access it, means that providers can avoid large costs of transmission over networks provisioned by third-party carriers.
• Critical infrastructures such as oil and gas facilities require the highest levels of precautions to avoid system failures that could escalate into catastrophes. Edge computing allows for data from temperature and humidity sensors, IP camera, pressure and moisture sensors, and handheld devices. The data is analyzed, processed, and then sent back to users in near real-time, helping them prevent malfunctions.

Edge computing is all about achieving geographical distribution so that computing power can be taken closer to the endpoints that need it most. So, instead of only relying on a dozen giant datacenters, edge computing provides for the cloud to come closer to places/people/devices where there’s a business case for reducing response times even by a few hundred microseconds.

Critical security and safety systems always need to function on premises. You need these systems to operate or fail in a safe state regardless of what happens to the cloud or the connection. The simplest on-premises approach is a big red shut-off button on each machine. Azure IoT Edge enables a more complex safety system.
Example: You monitor the temperature across a range of machines and if the combined temperature gets too high you need to shut down all machines to prevent damage or risk to human operators. A safety system at the level of the individual machine is not enough, because it can’t track combined temperature across multiple machines. Your safety system needs to be one level higher to monitor and control multiple machines, and you can do this with Azure IoT Edge.

• By 2020, it’s expected that there will be more than 5,600 million smart sensors and connected IoT devices across the globe.
• The data generated by these devices will be to the tune of 5,000+ zettabytes.
• The IoT market size is expected to reach $724 billion by the end of 2023.

Most of this data will be generated at enterprise endpoints located on the “edge” — such as sensors, machines, smartphones, wearable devices, etc. We can consider these to be located on the “edge” because they’re far away from the central datacenter of the organization.

This massive data can’t simply be relayed to the central server because it will overwhelm the entire network. Enterprises will implement edge computing so that massive data doesn’t have to be transported to corporate datacenters. Instead, advanced operational analytics will happen at the remote facilities, to enable site managers and individuals to act in real time on the available information.

Microsoft Windows 10 customers can now commercialize devices with new servicing options:
• A Semi-Annual Servicing Channel, offers two feature update releases per year,
• A Long-Term Servicing Channel, provides security and quality updates without any new features over a 10-year period. The long-term model is ideal for commercial IoT devices, including point-of-sale systems, ATMs, and industrial equipment controllers, which all require strong security and fewer feature updates.

A new cloud service subscription, called Windows 10 IoT Core Services, offers companies the services to commercialize a device on Windows 10 IoT Core, including both long-term OS support, and services to manage device updates and assess device health. This will help device manufacturers to lower support costs, and will help distributors create better business models to create customer value.

Microsoft has added the ability to do more work at the edge, including: machine learning, event processing, and image recognition, “Seamless integration with Azure IoT Edge brings cloud intelligence and analytics securely to Windows 10 IoT devices at scale,”

Windows Machine Learning allows developers to use pre-trained machine learning models in their applications, which can be evaluated and adjusted as needed at the edge.

Microsoft also added support for NXP i.MX 6, 7 and 8M series processors to Windows 10 IoT Core.

Windows 10 IoT also includes turnkey support for both Azure IoT Device Management and Microsoft Intune to provide more scalable device management for enterprise IoT deployments.

https://azure.microsoft.com/en-us/blog/microsoft-azure-enables-a-new-wave-of-edge-computing-here-s-how/

https://docs.microsoft.com/en-us/azure/iot-edge/about-iot-edge

https://www.zdnet.com/article/where-the-edge-is-in-edge-computing-why-it-matters-and-how-we-use-it/

The acatech Industrie 4.0 Maturity Index is a six-stage maturity model that analyses the capabilities in the areas of resources, information systems, culture and organisational structure that are required by companies operating in a digitalised industrial environment.

https://www.acatech.de/Publikation/industrie-4-0-maturity-index-managing-the-digital-transformation-of-companies/

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