Given the complexity and scale of this data, machine learning and AI are essential to accurately forecast and automate maintenance, which is why we need to have all the data aligned.

Machine learning (ML) can be applied at the ‘edge’ where data processing functions are tightly targeted and power consumption must be low.

Japanese researchers employed machine learning to develop a wireless power transfer system that remains stable under any load ...

When machine learning algorithms are fed a steady stream of real-time data, they can quickly detect bottlenecks, anomalies and other operational inefficiencies.