IIoT

In this previously published IoT Evolution article, Stratus’ VP of business line management, Jason Andersen, discusses how industrial IoT gateway systems can be adequate, but relying on them for business-critical use in production environments could introduce new levels of risk. It also includes his insight into how to manage this risk.

There’s no better time to work on building optimal foundations for future asset management strategies and IIoT than now. With easy-to-deploy OT solutions that also provide low-maintenance upkeep, IA environments can be well on their way to delivering the strongest results possible for their clients

As we see more and more convergence of OT and IT, we are also witnessing an increase in the challenges faced by today’s OT professionals. We’ve seen an influx of OT professionals continuously being asked to support complex environments and infrastructures with dwindling resources. Making them ideal candidates for a technological solution that brings simplicity and reliability to their day-to-day work.

In this previously published Automation World article, Stratus’ VP of business line management, Jason Andersen, discusses why artificial intelligence (AI) is important for industrial companies to be thinking about given the large amounts of data brought about by the Industrial Internet of Things (IIoT).

This article describes the evolution that is taking place in edge computing today, and briefly describes how next-generation solutions can help organizations capitalize on new opportunities presented by the edge.

The Industrial Internet of Things (IIoT) has many advantages for industrial organizations, enabling them to generate valuable business insights that can improve everything from efficiency to productivity. Read on to learn how to keep operations simple.

At first glance, edge computing appears very homogeneous, and includes all activities that are performed outside of the “Core”, which could be the location of the primary corporate-wide IT (Information Technologies) infrastructure. In fact, edge computing is a multi-tiered mix of assets arranged in a use-case and workload centric fashion. CIOs and other IT leaders must prepare their wider organization and key stakeholders for the necessary steps to successfully deploy and manage an edge computing infrastructure. Firms that acknowledge edge computing as a long-term investment generally fall into these two categories. To learn what the two categories are read on.

For many industrial automation professionals, the cloud has come to represent the backbone of the IIoT. But, for enterprises to really make progress with their IIoT visions, they must begin to realize that the cloud is only one part of their IIoT universe.

Organizations are becoming more focused on the data than on the applications – further recognizing that data and analytics have great potential for unlocking business value. To learn what’s driving this shift, read the full article here.

How IIoT can help reduce risk, as previously published in Food Quality & Safety by Jason Andersen. Knowing where to focus your IIoT efforts first and how it will pay off in the long run, manufacturers can make smart decisions when implementing the IIoT into existing processes. Read on to uncover the three main factors to consider.