From a technical point of view, I-IoT analytics uses multiple modules—machine learning (ML), anomaly detection, physics kernels, risk analysis, feature engineering, signal processing, optimization methods, simulation methods, damage prognostics, data quality and imputation, and surrogate-modelling. We can identify two way to build analytics, either based on practical rules or a mathematical model.
I-IoT analytics technologies
Rule-based
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. Rules-based analytics, for instance, can translate human knowledge or empirical rules into...
