December 7, 2022
The expansion of IoT over the last decade, the rollout of 5G, and the development of edge computing have all combined to create new opportunities for digital transformation, according to industry analysts from organisations such as Gartner and McKinsey and Co. Industrial systems, in particular, tended to be air-gapped from the wider organisation networks, and…

The expansion of IoT over the last decade, the rollout of 5G, and the development of edge computing have all combined to create new opportunities for digital transformation, according to industry analysts from organisations such as Gartner and McKinsey and Co.

Industrial systems, in particular, tended to be air-gapped from the wider organisation networks, and historically operated in a proprietary environment. But in recent years, as companies have sought to benefit from approaches like big data, IP networks have become more common, requiring a bridge across the air gap – with some obvious consequences.

According to Gartner, “The number of Internet of Things (IoT) devices is doubling every five years, creating security risks that must be mitigated.”

The comments were made in a paper examining the future of cloud and edge Infrastructure.

The analysts note the rapid acceleration of cloud computing – the term they use is “exploding”, – and they said that “enterprise applications are migrating to the public cloud and organisations becoming more cloud-native in their deployments.”

In this context, they note that “edge computing adoption is picking up pace as hyperscale cloud providers develop solutions to distribute their cloud capabilities closer to the edge.”
For its part, McKinsey and Co argue that like cloud, edge computing is becoming more mainstream.

In a paper examining how organisations are leveraging industrial IoT and advanced technologies to drive digital transformation

The firm identifies three factors it said are pushing computational capacity out of the cloud and onto operational sites.

Firstly, “Edge technologies have intermittent connectivity, which enables a wider range of features than ones that are fully online. [Secondly] sophisticated devices depend on real-time decision making, and [Thirdly] the computational decisions required do not rely on greater computing power.”

The management consultants identify sectors including travel, transportation and logistics, and retail, as having the most immediate potential, and McKinsey said that these currently provide almost a third of the existing use case environments.

Take the automotive sector as an example.

According to McKinsey, autonomous driving, connectivity, electrification, and shared mobility are the four key drivers of transformation in the sector and all require significant mobile networking and computing enhancements.

Greatest effect

The authors explained that autonomous driving may have the greatest effect since it necessitates higher onboard-computing power to analyse massive amounts of sensor data in real-time.

They said, “Other autonomous technologies, over-the-air (OTA) updates, and integration of third-party services will also require high-performance and intelligent connectivity within and outside of the car. Similarly, increasingly stringent vehicle safety requirements require faster, more reliable mobile networks with very low latencies.”

The authors note that while most current applications in the sector are architected around a single work location, that’s likely to change.

“In the future, they may use some combination of edge computing with onboard or cloud processing that delivers higher performance. For instance, smart traffic management systems may improve onboard decision-making by augmenting the vehicle’s sensor data with external data (for example, other vehicles’ telemetry data, real-time traffic monitoring, maps, and camera images).”

In such a scenario, McKinsey suggested the data from multiple locations is likely to be fused by the traffic management software.

“The final safety-related decision will be made onboard the vehicle. Ultimately, large amounts of real-time and non-real-time data may need to be managed across vehicles, the edge infrastructure, and the cloud to enable advanced use cases. In consequence, data exchanges between the edge and the cloud must be seamless.”

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