| CPC G06F 11/3476 (2013.01) [G06F 11/0751 (2013.01); G06F 11/0793 (2013.01); G06F 11/349 (2013.01); G06F 11/0706 (2013.01)] | 20 Claims |
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1. A method comprising:
collecting data corresponding to operation of a plurality of controllers from one or more devices;
predicting, using one or more machine learning algorithms, at least one of degradation and failure of one or more controllers of the plurality of controllers based, at least in part, on the data corresponding to the operation of the plurality of controllers;
identifying, using the one or more machine learning algorithms, one or more corrective actions to prevent the at least one of the degradation and the failure of the one or more controllers;
generating instructions comprising the one or more corrective actions, wherein the instructions are transmitted to at least one user device;
wherein the data corresponding to the operation of the plurality of controllers comprises historical data and live data;
wherein the one or more machine learning algorithms are trained with at least a portion of the historical data;
wherein the predicting comprises classifying at least a portion of the data corresponding to the operation of the plurality of controllers as critical, the classifying comprising using the one or more machine learning algorithms to identify one or more patterns for performance metric changes reaching a criticality level; and
validating an accuracy of the one or more machine learning algorithms by testing the one or more machine learning algorithms with testing data comprising a subset of the historical data and a subset of the live data;
wherein the steps of the method are executed by a processing device operatively coupled to a memory.
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