IIoT analytics technologies
From a technical point of view, IIoT analytics uses multiple modules—ML, anomaly detection, physics kernels, risk analysis, feature engineering, signal processing, optimization methods, simulation methods, damage prognostics, data quality and imputation, and surrogate modeling. We can identify two ways to build analytics, either based on practical rules or a mathematical model.
Rule-based analytics
Rule-based analytics use knowledge about a variable or a particular feature to build a decision-based algorithm. Rule-based analytics can either use expert systems, classifiers, or rule-based ML. Rule-based analytics, for instance, can translate human knowledge or empirical rules into an algorithm.
In Chapters 7, 8, 10, and 12, we already implemented a simple rule-based algorithm on AWS/Azure based on a simple threshold. A more complex algorithm might use fuzzy logic or Bayesian probabilities.
Model-based analytics
What is a model? A model...
