Automation at the Industrial IoT edge
Leverage edge technologies in good times and bad by using remote visualization, monitoring, access and management as well as artificial intelligence (AI), machine learning (ML) and analytical applications.
- Industrial Internet of Things (IIoT) edge software platforms help automation.
- Enabling technologies include remote visualization, monitoring, access, and management for artificial intelligence, machine learning and analytical applications.
- ARC Advisory Group used material from its recent “Industrial IoT Edge Software Platforms” market analysis report for this article.
Industrial Internet of Things (IIoT) edge solutions have risen in prominence not only to pre-process data for consumption by cloud-based applications, but also to overcome real deficiencies when extending their reach to target endpoint devices. IIoT edge solutions can solve real problems related to both the latency of edge-to-cloud communications and security and operational concerns regarding sending data to and from off-premise components of the infrastructure. They also provide support for the automation environment in areas such as protocol support, visualization, and support for vertical architectures.
Industrial IoT edge software platforms
Emerging IIoT edge software platforms can help manufacturers and other industrial organizations in good times and bad. Many end users today are looking for remote access solutions to reduce or eliminate personnel both on-premise and in the field as a result of their organizational responses to the COVID-19 pandemic.
As the global macroeconomic situation improves, ARC Advisory Group expects manufacturers will continue moving beyond basic remote access and visualization to more robust edge compute, particularly for artificial intelligence (AI), machine learning (ML), and analytics in pursuit of digitally transformed business improvement strategies.
The breadth of the industrial IoT edge value proposition extends from basic remote visualization, monitoring, access, and management to sophisticated AI, ML and analytical applications. Many solutions either currently embody or are evolving to deliver this breadth of capability, but end users can start now by leveraging these solutions to address the economic challenges of the COVID-19 pandemic.
Firms are leveraging edge solutions to reduce the number of personnel in facilities and traveling to remote sites. This trend is expected to continue as industry goes forward with the lessons learned during this difficult time. Adopting the entry-tier remote access capabilities will further position installations for future adoption of the more sophisticated solutions.
The expanding number of edge software solutions also necessitates taking a strong look at buying, rather than internally developing, an edge solution. ARC research shows many end users who started by building their own internal solutions encountered issues with managing, updating, scaling and overall maintenance. Internal development also entails significant activities in non-value-add areas, such as connectivity and infrastructure, when easy-to-use solutions are available and are often more cost-efficient.
Cloud providers influence edge technologies
As cloud-based enterprise applications have become the norm, and cloud solutions themselves extend to the edge to access their source data, the edge solutions from the cloud providers are becoming part of the selection process. IT organizations involved in the selection process also bring the cloud providers into the discussion.
End users evaluating edge solutions from the enterprise cloud players should take several factors into account. First is enterprise cloud-based solutions tend to represent more of a toolset vs. solution approach at the edge. This can require significant investments in time and development to tailor these more horizontal solutions to an installation, typically by the IT organization and data scientists.
There is also the issue of cloud lock-in all the way to the edge, which some end users look to avoid. Use of standard IT and OT tools is one way to offset this potential, as is incorporating open source solutions.
KEYWORDS: Automation, IIoT, edge computing, cloud
Industrial Internet of Things (IIoT) edge software platforms help automation.
Enabling technologies include remote visualization, monitoring, access, and management for artificial intelligence, machine learning and analytical applications.
ARC Advisory Group used material from its recent “Industrial IoT Edge Software Platforms” market analysis report for this article.
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ARC Advisory Group provides more on IIoT Edge at www.arcweb.com/technologies/industrial-iot-edge.
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