The Industrial Internet of Things (IIoT) is one of the most important global change trends related to digitalisation at the moment. People also talk about the fourth industrial revolution, which is associated with robotisation, digitalisation and artificial intelligence, in addition to the IIoT. 

IIoT solutions involve a continuously growing trend in which the number of devices and sensors connected to the information network is growing exponentially. Detailed and real-time data is collected from devices, machines, processes, buildings, traffic, people, etc. The data is used in diverse ways to develop the servicing and maintenance of devices and systems as well as processes, such as the automation and anticipation of work phases. On the other hand, the analysis of vast amounts of collected data allows for understanding complex chains of events, the causality between various events and things, and, at its best, the development of anticipatory algorithms related to events or the creation of new intelligent services.

MANAGING THE TECHNOLOGY STACK OF THE ENTIRE INDUSTRIAL IoT

The continuously increasing layer of data collection has been subject to particularly rapid advancement within the development of the IIoT, to make the measurement of hardware and process operations increasingly comprehensive, timely and accurate. Another rapidly advancing layer is the analysis layer concerning the collected data, which in reality is the most valuable aspect of IIoT solutions. Data collection should produce concrete value to support business decisions and process development.

Nodeon’s skills with the IIoT are versatile, and the personnel have implemented distributed device management and data collection solutions in critical infrastructure environments for nearly 20 years. At Nodeon, the IIoT technology field is managed comprehensively, from various device and sensor interfaces all the way up to automation processes, secure data transmission solutions, centralised situational awareness, control and management systems as well as data analysis.

Distributed data collection and hardware management

Centralised situational awareness

Data communication solutions

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