公开(公告)号：US11240641B1

公开(公告)日：2022-02-01

申请号：US17096357

申请日：2020-11-12

Applicant: Amazon Technologies, Inc.

Inventor： Sven Eberhardt ,  Shekhar Pareek ,  Aniruddha Basak ,  Charles Edwin Ashton Brett ,  Amir Salimi

IPC: H04W4/08 ,  H04W8/00 ,  H04W8/18 ,  H04W8/22 ,  H04W8/26 ,  H04L29/08

Abstract: Techniques for automatically combining devices into a single group of devices, and splitting devices into multiple groups of devices are described. A machine learning model may process device profile data, associated with devices registered to two different users, and determine the devices should be combined into a single group of devices. Such enables a user to control each of the devices, of the two different users, but providing user inputs to a single device of the group. The machine learning model may also process device profile data, associated with devices registered to a single user, and determine the devices should be split into two or more groups of devices. Such may decrease the likelihood that a system may inadvertently control a device not intended by a user.

公开(公告)号：US12051419B1

公开(公告)日：2024-07-30

申请号：US17706289

申请日：2022-03-28

Applicant: Amazon Technologies, Inc.

Inventor： Hongyang Wang ,  Amir Salimi ,  Siyuan Liu ,  Sara Parker Hillenmeyer ,  Meet Prakash Vadera ,  Sunny Singh ,  Chandra Prakash Konkimalla ,  Yishuai Li ,  Rajesh Bangaru Ravindranath ,  George Strajan ,  Marc Wetter ,  William Evan Welbourne ,  Paul Aksenti Savastinuk ,  Charles Edwin Ashton Brett ,  Arpit Jain

IPC: F24F11/30 ,  G06F40/211 ,  G10L15/22

CPC classification number: G10L15/222 ,  G06F40/211 ,  F24F11/30 ,  G10L2015/223 ,  G10L2015/225

Abstract: Systems and methods for device control using near real time learning are disclosed. For example, an automatic action is performed by a target device in response to a predefined condition being met. Thereafter, context data is gathered and utilized to determine whether a negative user reaction has been provided in response to performance of the automatic action. When a negative user reaction is determined, mitigating actions may be taken close in time to when the context data is received to prevent further negative user reactions.