Industrial IoT

Setting up a solid framework for the Industrial Internet of Things (IIoT) is at the heart of a long-term, robust environment for IIoT project development.

Today’s unprecedented levels of heterogeneity, volume, and connectivity call for IoT data management strategies that consider scale, data gravity, and integration.

The increasing complexity of IoT implementation scenarios and the number of actors involved in end-to-end IoT development efforts within a company have brought unprecedented challenges.

IoT implementation is a highly complex, costly, and time-consuming effort. So why should it make sense for so many companies to throw themselves into the uncertain journey of implementing IoT?

The use of Wireless Sensor Networks (WSN) in a variety of (Industrial) Internet of Things scenarios has gained popularity over the past years.

We can think about the data generated by an IoT device as going through three separate phases: the data creation itself, collection and organization, and making data valuable.

This article discusses the features of a decentralized IoT edge computing ecosystem.

It turns out that uniting IoT and sustainability can be a powerful way of reducing global emissions.

Successful IIoT implementation projects require two major actors: the engineer and the data scientist. Yet how do you bridge the gap between these two mindsets?

As a recent phenomenon, the emerging paradigm of the industrial IoT platform brings forth the promise of innovation and streamlining.