AI-Driven Sleep Mode Configuration for Power Optimization

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Solution Overview

Problem

Conventional device management approaches rely on static sleep mode settings based on limited temporal parameters, leading to inefficient power usage and increased electricity consumption.

Innovation Solution

The implementation of artificial intelligence techniques to determine power-related information, identify instances of inactivity, and generate sleep mode configuration modifications for devices, enabling automated transitions to sleep mode based on actual usage patterns.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by moving object

If static sleep mode settings based on limited temporal parameters are used, then device management is simple, but power consumption is high and electricity resources are wasted

Engineering Contradiction:

Improvepower consumptionVSAvoiddevice management complexity

Core Design Contradiction:

Use of energy by moving objectVSDevice complexity

Solution Approach 1:

The patent transitions from static sleep mode settings to dynamic, adaptive sleep mode configuration. The system continuously monitors device usage patterns and automatically adjusts sleep mode parameters (such as inactivity thresholds and transition timings) based on learned behavioral patterns, enabling power savings without requiring complex manual configuration by users.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements self-service through automated analysis of device usage patterns and autonomous adjustment of sleep mode settings. The device management system independently processes usage data, identifies optimization opportunities, and modifies sleep mode configurations without user intervention, eliminating the need for users to understand or configure complex power management parameters.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If static sleep mode settings with arbitrary temporal parameters are implemented, then configuration is straightforward, but electricity resources are wasted due to inability to adapt to actual usage patterns

Engineering Contradiction:

Improveadaptability to usage patternsVSAvoidelectricity resource waste

Core Design Contradiction:

Adaptability or versatilityVSLoss of energy

Solution Approach 1:

The system implements continuous feedback loops by monitoring device usage patterns and using this information to dynamically adjust sleep mode settings. The system processes usage data, compares actual patterns against configured parameters, and automatically refines sleep mode thresholds and timings to optimize power consumption while maintaining device availability when needed.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent dynamically changes sleep mode parameters such as inactivity thresholds, transition timings, and mode selection criteria based on analyzed usage patterns. Instead of fixed arbitrary values, the system adjusts these parameters continuously to match actual device usage behavior, reducing electricity waste while maintaining operational readiness when users typically need the device.

Inventive Principle:

Principle #35Parameter changes

3Loss of information

If conventional static sleep mode approaches are used, then implementation is simple, but power-related information and optimization opportunities are lost

Engineering Contradiction:

Improveusage pattern informationVSAvoidpower optimization efficiency

Core Design Contradiction:

Loss of informationVSProductivity

Solution Approach 1:

The system performs preliminary analysis of device usage patterns to identify future power optimization opportunities. By processing usage data and learning behavioral patterns in advance, the system can proactively adjust sleep mode settings before suboptimal power consumption occurs, maximizing energy savings while maintaining device availability when needed.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12117881B2Automated power-related device usage determinations using artificial intelligence techniques

Publication Date: 2024.10.15 DELL PROD LP

AI summary

Methods, apparatus, and processor-readable storage media for automated power-related device usage determinations using artificial intelligence techniques are provided herein. An example computer-implemented method includes determining power-related information for one or more devices by processing utilization data associated with the device(s) using artificial intelligence techniques; determining, based at least in part on the power-related information, multiple instances of inactivity and durations thereof for the device(s); determining at least one particular duration of inactivity for the device(s) based at least in part on a number of occurrences of each of the determined durations of instances of inactivity; generating, based at least in part on the at least one particular duration of inactivity, one or more sleep mode configuration modification recommendations for the device(s); and performing one or more automated actions based on the one or more sleep mode configuration modification recommendations.