Methods, devices, and computer program products for model adaptation

A method for model adaptation, comprising:

• deploying a trained machine learning model to a first computing device, by a second computing device, the machine learning model being configured to determine abnormality of a data set to be analyzed from a data collector, and the second computing device having a higher computing capability than the first computing device;
• receiving at least a portion of data in the data set from the first computing device;
• updating the machine learning model based on the received portion of data;
• and
• redeploying the updated machine learning model to the first computing device;
• wherein the first computing device comprises an edge computing node;
• and
• wherein the second computing device comprises a cloud computing device.

An apparatus comprising at least one of a first electronic device and a second electronic device, the first electronic device comprising:

• at least one processor;
• and
• at least one memory storing computer program instructions, the at least one memory and the computer program instructions being configured, with the at least one processor, to cause the first electronic device to perform acts comprising:
• receiving a data set to be analyzed from a data collector;
• determining abnormality of the data set using a machine learning model deployed at the first electronic device;
• transmitting, based on the determined abnormality of the data set, at least a portion of data in the data set to a second electronic device for update of the machine learning model, the second electronic device having a higher computing capability than the first electronic device;
• and
• obtaining redeployment of the updated machine learning model from the second electronic device;
• wherein the first electronic device comprises an edge computing node;
• and
• wherein the second electronic device comprises a cloud computing device.