公开(公告)号：US11848027B2

公开(公告)日：2023-12-19

申请号：US17306004

申请日：2021-05-03

申请人： SAP SE

发明人： Kavitha Krishnan ,  Nicholas John Nicoloudis ,  Luxi Li ,  Pai-Hung Chen ,  Anton Kroger

IPC分类号： G10L25/30 ,  G06N3/04 ,  G06N3/08 ,  G10L19/02 ,  G10L25/87

CPC分类号： G10L25/30 ,  G06N3/04 ,  G06N3/08 ,  G10L19/0212 ,  G10L25/87

摘要： In some example embodiments, there may be provided a method that includes receiving a machine learning model provided by a central server configured to provide federated learning; receiving first audio data obtained from at least one audio sensor monitoring at least one machine located at the first edge node; training, based on the first audio data, the machine learning model; providing parameter information to the central server in order to enable the federated learning among a plurality of edge nodes; receiving an aggregate machine learning model provided by the central server; detecting an anomalous state of the at least one machine. Related systems, methods, and articles of manufacture are also described.

公开(公告)号：US20220351744A1

公开(公告)日：2022-11-03

申请号：US17306004

申请日：2021-05-03

申请人： SAP SE

发明人： Kavitha Krishnan ,  Nicholas John Nicoloudis ,  Luxi Li ,  Pai-Hung Chen ,  Anton Kroger

IPC分类号： G10L25/30 ,  G06N3/04 ,  G06N3/08 ,  G10L25/87 ,  G10L19/02

摘要： In some example embodiments, there may be provided a method that includes receiving a machine learning model provided by a central server configured to provide federated learning; receiving first audio data obtained from at least one audio sensor monitoring at least one machine located at the first edge node; training, based on the first audio data, the machine learning model; providing parameter information to the central server in order to enable the federated learning among a plurality of edge nodes; receiving an aggregate machine learning model provided by the central server; detecting an anomalous state of the at least one machine. Related systems, methods, and articles of manufacture are also described.