Predictive Power Saving for Computing Devices
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Solution Overview
Problem
Existing power management techniques in computing devices often lead to a poor user experience by unnecessarily dimming or shutting down the screen and transitioning to hibernation states, as they rely solely on battery life without considering the availability of a power source, resulting in inconvenience to users.
Innovation Solution
A method that predicts the availability of a power source by analyzing user behavior, calendar events, and location data, allowing the device to adjust power management settings to prevent unnecessary transitions to reduced power states when a power source is expected to be available, thereby maintaining a full active state without power restrictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the computing device transitions to a reduced power state when battery charge is low, then power consumption is reduced and battery life is prolonged, but user convenience deteriorates due to unnecessary interruptions when a power source is available
Solution Approach 1:
The system performs preliminary actions by predicting future power source availability based on user behavior patterns, calendar events, and location data before making power state transition decisions. This allows the device to anticipate when power will be available and avoid unnecessary transitions to reduced power states, thereby maintaining user convenience while still optimizing power consumption when appropriate.
2Use of energy by moving object
If the device monitors user input to determine power management actions, then power saving is achieved, but user experience deteriorates due to screen dimming during active use
Solution Approach 1:
The system incorporates feedback mechanisms by continuously monitoring user input and device usage patterns to dynamically adjust power management decisions. By analyzing real-time user behavior feedback alongside predicted power source availability, the system can distinguish between intentional inactivity (when power saving is appropriate) and active use (when power saving should be avoided), thus achieving power savings without degrading user experience.
Data Source
AI summary
A method includes receiving an instruction to transition a device into a reduced power state, predicting an availability of a power source determining a charge of a power storage element, determining whether the power source is predicted to be available before the charge of the power storage element falls below a threshold value, upon determining that the power source is predicted to be available before the charge of the power storage element falls below the threshold value, preventing the transition of the device into the reduced power state, and upon determining that the power source is not predicted to be available before the charge of the power storage element falls below the threshold value, transitioning the device into the reduced power state.