A new white paper from the Industrial Internet Consortium (www.iiconsortium.org) , titled, “Making Factories Smarter Through Machine Learning,” offers a great read on how machine learning can allow for better edge analytics, reduce data streams and promote better data fidelity.
A passage from the White Paper below:
The other capability provided by the software is the ability to read complex sensors and perform pre-processing in terms of data reduction: For example, vibration is sampled at least two times the vibration frequency. In this case, a fast Fourier transform is performed and only the frequency of interest is stored. This is an area where there is high opportunity for more efficient processing – effectively using machine learning for pre-processing and feature selection.
Therefore, it (SoC) can sample each variable with smart criterions: For example, temperature may not be measured with the same frequency of vibration
The white paper provides a real roadmap solution on how to move from preventive, SoC machine learning and simple industrial networking solutions to make this happen. The link to the white paper can be found here.
Industrial Internet Consortium