AI and hybrid edge–cloud solutions predicted to dominate IIoT in 2022
UK IoT edge software company IOTech has made four main predictions for edge computing in 2022. Among its forecasts, the company foresees a proliferation of AI and machine learning at the IOT edge and edge-cloud architectures as the norm.
The company also believes that 5G’s impact on edge computing will probably increase, but that it is still too early to predict.
“This past year, we’ve seen edge computing emerge from pilot programs to deployments,” said Jim White, CTO, IOTech. “We believe 2022 will be the year that edge computing is fully integrated into the architecture of every major industrial IoT system.”
IOTech’s 2022 predictions are related to technology advancements, architectures and impact to industries.
Prediction 1: There will be pervasive adoption of AI/ML at the edge
The new status quo will be that edge systems will incorporate AI and machine learning. Simple rules engines and edge analytics are already at the edge, but today organisations demand more intelligence at the edge. The raw compute to run AI/ML at the edge was previously a limiting factor, but this is no longer the case. While training ML systems will occur largely in the cloud or in the enterprise, ML models running on lighter AI runtime engines at the edge are more commonplace and will soon be the norm. Visual inference has been a leading use case, but other AI/ML solutions will soon follow. Edge platform providers will play a key role in developing solutions that can easily integrate AI/ML technologies.
Prediction 2: Hybrid edge–cloud architectures will be the norm
It’s not edge compute ‘or’ cloud compute, it’s more a case of ‘and’. Organisations are finding that processing data needs to be performed at the edge as well as in the cloud or enterprise. Although initially there was much excitement related to the cloud providers reaching down to the edge, the reality is that there are significant challenges in moving all edge data to the cloud and performing all the processing in the cloud. The cost of data transport, latency issues and security/data privacy concerns are among the chief challenges. Likewise, the raw processing power of the edge and the ability to do deeper exploration of the edge data over longer periods of time for better insights means edge computing alone is not a solution. Solutions must allow for the right processing at the right levels, and this calls for hybrid edge–cloud architectures.
Prediction 3: The industrial sector emerges from edge/IOT research mode
The industrial sector is becoming focused and organised in its effort to offer new solutions at the IoT edge. Businesses in manufacturing, building automation, and smart energy are in full ‘build’ or ‘buy’ mode for IoT edge solutions. Many large industrial-sector businesses are fully committing to grow their edge/IoT products and strategy.
Prediction 4: End users will demand solutions rather than pieces/parts
Companies looking to benefit from edge/IoT technology are looking for more fully integrated solutions. They want immediate tangible business outcomes and are not interested in receiving a bucket of technology parts that they have to pull together themselves. For system integrators, it means developing the right technology partnerships to pre-assemble and deliver complete solutions to customers. Integrators will naturally gravitate to edge products that are inherently more open and flexible as these will be easier to integrate and adapt to more use cases.
In addition to these predictions, the company also offered these insights:
Traditional IT hardware OEMs will need to develop edge/IOT strategies
Edge solutions don’t start with the selection of IT hardware. They start by addressing the challenge that is being solved or the outcome that is needed and then building the right system to meet these requirements. As the IoT edge becomes ubiquitous, all layers of the architecture need to be an effective part of the solution. Traditional hardware OEM vendors need to ensure they have a vision and strategy in the edge/IOT space or risk becoming irrelevant or a commodity to edge customers.
Digital twin standards are needed to ensure pace of innovation
The current lack of a digital twin standard is hampering adoption and requiring organisations to roll their own interoperability solutions or be locked into a single provider’s implementation. With digital twin technology increasingly becoming a sought-after part of the IoT solution, a standard is the next logical and crucial step to drive innovation.
Noise level for edge and 5G will continue
From an edge platform perspective, 5G provides a bigger, stronger, less-latent pipe between the edge and the enterprise or cloud. Because it can reduce latency, 5G can allow more processing to occur in the cloud. 5G could become more interesting to edge/IoT solution providers as telcos work towards implementation of private (or semi-private) 5G installations in that allow more ‘things’ to be connected but in a secure and isolated way.
COVID-19 sped up existing challenges
Supply chain issues and human resources challenges were already beginning to be exhibited prior to the pandemic, and COVID-19 accelerated and heightened these issues for organisations. As businesses and industries emerge from the pandemic, 2022 cannot be a return to normal. Companies must innovate and use technology to address the aforementioned challenges. Therefore, IOT edge adoption will accelerate. It will be the year that companies transition from research and pilot programs to launches and deployments at scale.
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