5G, Edge, and Industry 4.0 Q&A

The confluence of 5G networks, AI and machine learning, industrial IoT, and edge computing are driving the fourth industrial revolution – Industry 4.0. The impact of the industrial edge and how it is being transformed were among the topics at our SNIA Cloud Storage Technologies Initiative (CSTI) webcast “5G Industrial Private Network and Edge Data Pipelines.” If you missed it, you can view it on-demand along with the presentation slides in the SNIA Educational Library. In this blog, we are sharing and clarifying answers to some of the intriguing questions from the live event.

Q. What are some of the key challenges to support the agility and flexibility requirements of Industry 4.0?

A. The fourth industrial revolution aka Industry 4.0 aspires to fundamentally transform the flexibility, versatility and productivity of future smart factories. Key attributes of this vision include complex workloads to enable remote autonomous operation, which involves autonomous mobile robots and machines, augmented reality aided connected workers, wireless sensors, actuators and remote supervisory control systems, as shown in the diagram below. Machines in smart factories will no longer be stationary. To enable quick response to supply demand changes and enable mass customization (“batch size of one”), factory lines need to be quickly reconfigurable and need machines to move within a certain range. These AI-based, mobile autonomous robots and machines require high data through-put wireless networks and highly reliable sub-second latency for machine-to-machine control communications.

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5G Industrial Private Networks and Edge Data Pipelines

The convergence of 5G, Edge Compute and Artificial Intelligence (AI) promise to be catalyst for continued digital transformation. For many industries, it will be a game-changer in term of how business in conducted. On January 27, 202, the SNIA Cloud Storage Technologies Initiative (CSTI) will take on this topic at our live webcast “5G Industrial Private Networks and Edge Data Pipelines.”

Advanced 5G is specifically designed to address the needs of verticals with capabilities like enhanced mobile broadband (emBB), ultra-reliable low latency communications (urLLC), and massive machine type communications (mMTC), to enable near real-time distributed intelligence applications. For example, automated guided vehicle and autonomous mobile robots (AGV/AMRs), wireless cameras, augmented reality for connected workers, and smart sensors across many verticals ranging from healthcare and immersive media, to factory automation.

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5G Streaming Questions Answered

The broad adoption of 5G, internet of things (IOT) and edge computing are reshaping the nature and role of enterprise and cloud storage. Preparing for this significant disruption is important. It’s a topic the SNIA Cloud Storage Technologies Initiative covered in our recent webcast “Storage Implications at the Velocity of 5G Streaming,” where my colleagues, Steve Adams and Chip Maurer, took a deep dive into the 5G journey, streaming data and real-time edge AI, 5G use cases and much more. If you missed the webcast, it’s available on-demand along with a copy of the webcast slides.

As you might expect, this discussion generated some intriguing questions. As promised during the live presentation, our experts have answered them all here.

Q. What kind of transport do you see that is going to be used for those (5G) use-cases?

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