General Electric Company
MODEL SHARING AMONG EDGE DEVICES

Abstract:

The example embodiments are directed to a system and method for sharing machine learning model parameters among edge devices in a clustered group of edge devices sensing data about an industrial asset. In one example, the method may include one or more of storing unique parameters of a machine learning (ML) model associated with an industrial asset which are unique with respect to unique parameters of other edge systems in the group of edge systems, receiving common parameter information from the group of edge systems which is shared among the group of edge systems, generating updated parameter values for an ML model based on a combination of the unique parameters and the received common parameter information, and executing the updated ML model based on incoming data from the industrial asset to generate predictive information about the industrial asset.