Apparatus and Method for System Profile Learning in an Information Handling System

A method comprising:

• providing, by a processing system of an information handling system, first sensor data from a first sensor of the processing system to a management system of the information handling system;
• providing, by the processing system, second sensor data from a second sensor of the processing system to the management system;
• determining, by a prediction module of the management system, based on a prediction algorithm and a learned model of a learned model table entry associated with the processing system, an estimate of a first value of the first sensor data using a second value of the second sensor data;
• determining, by the prediction module, a residual of the first value by a comparison of the estimate to the first value;
• determining, by the prediction module, a significance of the residual, based on the learned model and a first sensor data history of the learned model table entry, wherein the significance having a significant value is associated with a predicted anomaly;
• determining, by the prediction module, that an anomaly table entry in an anomaly table has a known anomaly class for the predicted anomaly, based on the first value, the second value, and known anomaly classes in the anomaly table, in response to the significance having a significant value;
• performing, by the prediction module, a remediation plan of the anomaly table entry to resolve the predicted anomaly in response to determining the known anomaly class;
• and
• receiving, by the management system, third sensor data from a third sensor of the processing system, wherein the first sensor data includes a fan speed of a fan, the second sensor data includes a processor temperature of a processor, the third sensor data includes a processor utilization of the processor, and the predicted anomaly includes a clogged heat-sink.

A method comprising:

• providing, by a processing system of an information handling system, first sensor data from a first sensor of the processing system to a management system of the information handling system;
• providing, by the processing system, second sensor data from a second sensor of the processing system to the management system;
• determining, by a prediction module of the management system, based on a prediction algorithm and a learned model of a learned model table entry associated with the processing system, an estimate of a first value of the first sensor data using a second value of the second sensor data;
• determining, by the prediction module, a residual of the first value by a comparison of the estimate to the first value;
• determining, by the prediction module, a significance of the residual, based on the learned model and a first sensor data history of the learned model table entry, wherein the significance having a significant value is associated with a predicted anomaly;
• determining, by the prediction module, that an anomaly table entry in an anomaly table has a known anomaly class for the predicted anomaly, based on the first value, the second value, and known anomaly classes in the anomaly table, in response to the significance having a significant value;
• performing, by the prediction module, a remediation plan of the anomaly table entry to resolve the predicted anomaly in response to determining the known anomaly class;
• and
• determining, by the prediction module, the estimate of the fan speed using the processor temperature and the processor utilization based on the prediction algorithm and the learned model, wherein the prediction algorithm includes a multi-variant least square algorithm;
• wherein:
• determining the significance further includes utilizing fan speed outlier information and fan speed threshold information from the first sensor data history;
• and
• the first sensor data history includes a fan sensor data history.