The role of Internet of Things (IoT) in industrial applications is continuously changing, fast and getting more diverse. With the expanding use cases of Industrial IoT (IIoT), the definition and nature of ‘things’ has also undergone paradigm shifts in recent years. In numerous diverse end-use verticals, including manufacturing, telecommunications, finance, and healthcare, efforts are underway to adapt the network architectures to fit the changing requirements, with an aim to gain better operational visibility. The function and responsibilities of network edge devices used in IIoT is also changing. New roles seem to emerge for the IIoT ‘things’ that are assuming the role of these devices in the edge computing framework.

Role of Automation Need to Evolve for Monitoring and Analytics to be Useful in IIoT

A growing number of IIoT ‘things’ are becoming an integral part of brownfield assets world over, and developing IIoT network for them needs to reflect these changes, according to a CTO executive in B+B SmartWorx, a U.S-based electronics manufacturers offering solutions on connected intelligence. He makes an important revelation that the role of automation needs to evolve beyond the traditional functionalities, in order for monitoring and analytics applications to make some sense in the area IIoT.

Intelligence in IIoT from Consumer Data Pushed to Edge of Network

The things in IIoT need to be configured, with a focus to gain ‘intelligence’ built around data—which tells them what data to publish and when to publish. The independent thinking needs to evolve, with the focus of loosening the hold of master or control devices in IIoT on the data. Typically, in IIoT, the data traditionally lies in a remote application. Recent trends highlight that a growing volume of IIoT consumer data in edge network, consisting of micro-data centers, are usually being pushed to a device gateway onto to a central data center or cloud storage repository.

Advances in technology, underpinned by miniaturization of electronics, has made this possible by putting memory, processors, and network stacks in small manageable compartments, normally devices, that also calls for new skills. This bodes well for the IIoT market.