As part of the rise of the Industrial Internet, all machinery, transportation and facilities are being equipped with a new generation of instruments and sensors that generate petabytes of data and that, thanks to the advance of artificial intelligence and Edge Computing, make it possible to implement predictive maintenance applications with real-time responsiveness.
We are still at the dawn of Machine Learning and Artificial Intelligence in the Industry. Still, as we envision new use cases and develop them in our environment, we realise success in the future depends on the proper implementation today.
Moving towards a decentralized, intelligent and cybersecure Smart Grid involves a series of challenges that we explain in our new site
Advances in Artificial Intelligence continue to act as a driver of the industry's digital transition. With the power of AI and analytics pushing into IT operations, it is only a matter of time before artificial intelligence is integrated throughout all industrial processes.
The growth of Edge technology is causing a revolution on the path to Industry 4.0, and the need has arisen to define different parts of the Edge and their functionalities. Concepts such as thin edge and thick edge have emerged from the exponential growth of Edge Computing technology, which industry experts claim is the key to the digital transformation of critical industrial infrastructures.
The energy sector is undergoing a profound transformation and Edge Computing is positioned as one of the enabling technologies to manage an increasingly distributed energy.