Diverse requirements of 5G services command co-creation beyond telecoms
Massive support for the internet of things is a major aspect of 5G. And we’re not talking about consumer IoT like wearables or smart home devices; we’re talking about billions of devices driving digital transformation for enterprise and industrial interests looking to streamline operations to realize cost efficiencies and revenue benefits. Given this paradigm—the need for telcos to create bespoke services for wildly variant application, the stage is set for innovation.
Susan Welsh de Grimaldo of Strategy Analytics explained it this way during a recent conversation at 5G World in London. “I think what’s really exciting with 5G is the ability to do co-creation…pulling in various industries that have very different dynamics and needs, and understanding how to develop to that with 5G.”
She noted the role artificial intelligence, machine learning and distributed computing in the broader context of 5G. “We’re creating a platform for innovation and for pulling in other players to help define how they actually want to use these networks. I think the innovation, it’s gong to be very exciting to see.”
Rainer Leibhart, Nokia’s head of 5G solution architecture, described two categories of innovation. On the radio and core side, “We need definitely new features coming up with 5G to cope with the, let’s say, diverse requirements…This is one challenge. The other thing is more when we are talking about this machine learning, artificial intelligence, so how to cope with the immense, let’s say, data traffic, the amount of data coming in. It’s taking the data coming from IoT machines, doing machine learning or putting machine learning algorithms on top of this data. On that basis we are generating new procedures and services around IoT traffic.”
To give a hypothetical that demonstrates the role of edge intelligence for an IoT implementation, let’s think about a remote mining site kitted out with sensors that monitor things like asset performance and environmental conditions. Some of that data needs to be analyzed in near real-time at the edge because it could have a straight line to operational performance and life safety. Data that’s valuable but not necessarily mission critical can go back to the cloud for retention to create a long-term picture of operational KPIs.
And that’s the point, according to Caroline Chan, VP and GM of Intel’s 5G Infrastructure Division. “The machine learning, the AI, what it does is it really improves significantly the operational efficiency.” She pointed out the approval for a merger of AT&T and Time Warner, which will further help diversify the traditionally operator business into a more integrated service provider and media company. “The way that I think about it, a lot of these telco companies, if done right, they all become some sort of webscale company.”
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