Power Mode Heuristics Based on User Behavior Backoff

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Solution Overview

Problem

Current computing devices lack an intelligent power management system that dynamically adjusts power states based on user behavior and habits, leading to inefficient power consumption.

Innovation Solution

A method and apparatus that monitor user behavior and habits to determine when to transition a computing device into a reduced power mode, using a power manager that considers both current activity and historical data to optimize power usage without compromising user experience.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by moving object

If the computing device operates in full power mode by default, then functionality and user experience are maintained, but power consumption is high

Engineering Contradiction:

Improvepower consumptionVSAvoidresponsiveness to user needs

Core Design Contradiction:

Use of energy by moving objectVSAdaptability or versatility

Solution Approach 1:

The system dynamically transitions between different power modes (full power, reduced power, standby) based on real-time user behavior monitoring and historical habit analysis, making the power state adaptable rather than static

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system continuously monitors user behavior, compares it against historical habits, and uses this feedback loop to intelligently determine when to transition to or from reduced power modes, ensuring user needs are met while optimizing power consumption

Inventive Principle:

Principle #23Feedback

2Use of energy by moving object

If the computing device enters reduced power mode based on inactivity, then power consumption is reduced, but user experience may be compromised if the device wakes too frequently

Engineering Contradiction:

Improvepower consumptionVSAvoidconsistency of power management

Core Design Contradiction:

Use of energy by moving objectVSReliability

Solution Approach 1:

The system performs preliminary analysis of user habits and behavior patterns before making power mode decisions, using historical data to predict when reduced power mode is appropriate and when the user is likely to return

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system learns from user behavior patterns and automatically adjusts power management decisions without requiring explicit user input, improving consistency over time as it better understands user habits

Inventive Principle:

Principle #25Self-service

3Ease of manufacture

If the computing device uses traditional timeout-based power management, then implementation is simple, but power savings are limited due to inability to account for user habits

Engineering Contradiction:

Improveimplementation complexityVSAvoidpower consumption

Core Design Contradiction:

Ease of manufactureVSUse of energy by moving object

Solution Approach 1:

The system automatically monitors user behavior and learns habits without requiring manual configuration or user input, making the advanced power management self-configuring and reducing implementation complexity despite the sophisticated algorithms used

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS9348399B2Heuristics based on backoff for power modes

Publication Date: 2016.05.24 GOOGLE LLC

AI summary

According to one general aspect, a method may include monitoring, by a computing device, a user's current behavior in regards to the computing device. The method may also include determining whether to place the computing device in a reduced power mode based upon the user's monitored current behavior and based on a history of user habits in regards to one or more computing devices. In various implementations, the method may further include, if it is determined to place the computing device in the reduced power mode, placing the computing device in the reduced power mode.