Techniques for adjusting computing device sleep states using onboard sensors and learned user behaviors

US2020012331A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2020012331-A1
Application numberUS-201916578132-A
CountryUS
Kind codeA1
Filing dateSep 20, 2019
Priority dateJun 2, 2017
Publication dateJan 9, 2020
Grant date

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  1. Title

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  2. Abstract

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  4. Key dates

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  5. First independent claim

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Abstract

Official abstract text for this publication.

This application relates to techniques that adjust the sleep states of a computing device based on user proximity detection procedures. The technique includes detecting a first pattern, using a first subset of sensors of one or more sensors coupled to the computing device, to determine if the object is proximate to the computing device. Provided the first pattern is not indicative of the object being proximate to the computing device, the technique detects a second pattern, using a second subset of sensors of the one or more sensors, to determine if the object is proximate to the computing device. Furthermore, provided either the first pattern or the second pattern is indicative of the object being proximate to the computing device and provided a first portion of a computer system within the computing device is operating within a low-power sleep state, the technique causes the first portion to enter into a high-power sleep state.

First claim

Opening claim text (preview).

What is claimed is: 1 . A method for adjusting sleep states of a computing device based on a usage profile of the computing device, the method comprising, at the computing device: monitoring usage levels of the computing device over a period of time to establish the usage profile; in response to identifying, based on the usage profile, that the computing device is likely to be utilized within a first period of time: scheduling the computing device to transition, at a first time prior to the start of the first period of time, from a low-power sleep state into a higher-power sleep state. 2 . The method of claim 1 , further comprising, in response to identifying, based on the usage profile, that the computing device is unlikely to be utilized within a second period of time: scheduling the computing device to transition, at a second time subsequent to the start of the second period of time, from the higher-power sleep state into the low-power sleep state. 3 . The method of claim 2 , further comprising, in response to identifying that the computing device is being utilized between the start of the second period of time, but subsequent to the second time: cancelling the scheduling of the computing device to transition from the higher-power sleep state into the low-power sleep state. 4 . The method of claim 1 , further comprising, in response to identifying that the computing device has transitioned from the low-power sleep state into the higher-power sleep state prior to the first time: cancelling the scheduling of the computing device to transition from the low-power sleep state into the higher-power sleep state. 5 . The method of claim 4 , further comprising: updating the usage profile to reflect cancelling the scheduling. 6 . The method of claim 3 , further comprising: updating the usage profile to reflect cancelling the scheduling. 7 . The method of claim 1 , wherein monitoring usage levels of the computing device comprises analyzing obtaining at least one of the following inputs: keyboard input, mouse input, gamepad input, touch-sensitive surface input, or network input. 8 . The method of claim 1 , wherein the low-power sleep state causes the computing device to function in a mode in which at least one component included in the computing device is supplied with less a decreased amount of power relative to that which is supplied to the at least one component when the computing device is in an awake state. 9 . At least one non-transitory computer readable storage medium configured to store instructions that, when executed by at least one processor included in a computing device, cause the computing device to adjust sleep states based on a usage profile of the computing device, by carrying out steps that include: monitoring usage levels of the computing device over a period of time to establish the usage profile; in response to identifying, based on the usage profile, that the computing device is likely to be utilized within a first period of time: scheduling the computing device to transition, at a first time prior to the start of the first period of time, from a low-power sleep state into a higher-power sleep state. 10 . The at least one non-transitory computer readable storage medium of claim 9 , wherein the steps further include, in response to identifying, based on the usage profile, that the computing device is unlikely to be utilized within a second period of time: scheduling the computing device to transition, at a second time subsequent to the start of the second period of time, from the higher-power sleep state into the low-power sleep state. 11 . The at least one non-transitory computer readable storage medium of claim 10 , wherein the steps further include, in response to identifying that the computing device is being utilized between the start of the second period of time, but subsequent to the second time: cancelling the scheduling of the computing device to transition from the higher-power sleep state into the low-power sleep state. 12 . The at least one non-transitory computer readable storage medium of claim 9 , wherein the steps further include, in response to identifying that the computing device has transitioned from the low-power sleep state into the higher-power sleep state prior to the first time: cancelling the scheduling of the computing device to transition from the low-power sleep state into the higher-power sleep state. 13 . The at least one non-transitory computer readable storage medium of claim 9 , wherein monitoring usage levels of the computing device comprises analyzing obtaining at least one of the following inputs: keyboard input, mouse input, gamepad input, touch-sensitive surface input, or network input. 14 . The at least one non-transitory computer readable storage medium of claim 9 , wherein the low-power sleep state causes the computing device to function in a mode in which at least one component included in the computing device is supplied with less a decreased amount of power relative to that which is supplied to the at least one component when the computing device is in an awake state. 15 . A computing device configured to adjust sleep states of based on a usage profile of the computing device, the computing device comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the computing device to perform steps that include: monitoring usage levels of the computing device over a period of time to establish the usage profile; in response to identifying, based on the usage profile, that the computing device is likely to be utilized within a first period of time: scheduling the computing device to transition, at a first time prior to the start of the first period of time, from a low-power sleep state into a higher-power sleep state. 16 . The computing device of claim 15 , wherein the at least one processor further causes the computing device to perform steps that include, in response to identifying, based on the usage profile, that the computing device is unlikely to be utilized within a second period of time: scheduling the computing device to transition, at a second time subsequent to the start of the second period of time, from the higher-power sleep state into the low-power sleep state. 17 . The computing device of claim 16 , wherein the at least one processor further causes the computing device to perform steps that include, in response to identifying that the computing device is being utilized between the start of the second period of time, but subsequent to the second time: cancelling the scheduling of the computing device to transition from the higher-power sleep state into the low-power sleep state. 18 . The computing device of claim 15 , wherein the at least one processor further causes the computing device to perform steps that include, in response to identifying that the computing device has transitioned from the low-power sleep state into the higher-power sleep state prior to the first time: cancelling the scheduling of the computing device to transition from the low-power sleep state into the higher-power sleep state. 19 . The computing device of claim 15 , wherein monitoring usage levels of the computing device comprises analyzing obtaining at least one of the following inputs: keyboard input, mouse input, gamepad input, touch-sensitive surface input, or network input. 20 . The computin

Assignees

Inventors

Classifications

  • Services making use of location information · CPC title

  • Collaborative creation, e.g. joint development of products or services · CPC title

  • the I/O peripheral being a single or a set of motion sensors for pointer control or gesture input obtained by sensing movements of the portable computer · CPC title

  • controlling an operation mode according to history or models of usage information, e.g. activity schedule or time of day · CPC title

  • Input arrangements through a video camera · CPC title

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What does patent US2020012331A1 cover?
This application relates to techniques that adjust the sleep states of a computing device based on user proximity detection procedures. The technique includes detecting a first pattern, using a first subset of sensors of one or more sensors coupled to the computing device, to determine if the object is proximate to the computing device. Provided the first pattern is not indicative of the object…
Who is the assignee on this patent?
Apple Inc
What technology area does this patent fall under?
Primary CPC classification G06F1/3231. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Jan 09 2020 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).