Skip to main content

How Legacy Industrial IT Networks will Adapt and Evolve

The ongoing adoption of an emerging Internet of Things (IoT) within mainstream industrial settings will result in a substantial growth of the number of connected industrial devices. In particular, industrial control devices, such as programmable logic controllers (PLCs).

According to the latest global market study by ABI Research, over the period from 2014 to 2020, the number of connected industrial controllers will triple -- growing at an average rate of 20 percent.

"Compared to the general-purpose conventional networks, industrial networks are characterized by a large variety of technologies and communication protocols, whose combination is determined by the requirements of the specific application they address," said Eugenio Pasqua, research analyst at ABI Research.

As a consequence, there is typically little interoperability with conventional networks, but also between different industrial networks. ABI believes that sharing data among different facilities or with the higher levels of an enterprise remains a very challenging task within this context.

The technological advances of the past decade are, however, slowly changing this. The diffusion of Ethernet and IP-based industrial protocols, as well as the improved intelligence of industrial devices, have reduced the differences between conventional and industrial networks.

This progress enables an easier interconnection between enterprise IT applications and OT systems, including the industrial equipment and the associated software -- such as SCADA.

Firms like ABB, Siemens, Schneider Electric, and Rockwell Automation are among the major specialized IT systems providers that are helping industrial organizations adapt to this technological shift.

Through the adoption of open source software and other IoT technologies, industrial organizations can now make better use of the huge amount of data generated inside their facilities and extract more meaningful information.

Moreover, progressive big data analytics applications will enable a better view of what happens along the whole supply chain, achieving better performance at lower operating costs and offer the ability to react faster to environmental changes.

The number of potential benefits, as well as the increasing pressure from the rapidly evolving market, are pushing industrial organizations towards this direction.

In the foreseeable future, we will witness more and more industrial facilities opening up their information silos and sharing their data with the higher levels of the enterprise, connecting their operational and business domains in the process.

Popular posts from this blog

AI Agents Have Memory. Where is The Security?

Enterprise AI adoption keeps running into the same wall: the moment sensitive data, model weights, or agent memory leave a tightly controlled environment, security teams lose visibility into what happens to them while the workload is actually running. Confidential computing exists to close that gap, and new research from ABI Research shows the technology has matured enough, across CPUs, GPUs, containers, and now agentic AI, to become a foundational requirement for enterprises building sovereign AI infrastructure: computing environments they control end to end rather than simply rent. Protection is Moving From CPUs to GPUs ABI Research finds that CPU-based confidential computing is closest to mass-market adoption, the product of years spent hardening chip-level isolation for general workloads. GPU-based confidential computing is now generating the strongest momentum, and for good reason. It addresses one of the largest unresolved gaps in AI security: protecting data and models while inf...