Power Mode Transition Using Remote Sensor Activity Data
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Solution Overview
Problem
Existing computing devices do not effectively consider a user's intention to use the device when managing power, leading to unnecessary power consumption and prolonged reload times when resuming from suspended mode.
Innovation Solution
A computer-implemented method that switches a computing device between normal, power-saving, and warming modes based on activity data from a mobile device, using network circuitry to monitor for activity data and adjust power states accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the computing device enters suspend mode to save power, then power consumption is reduced, but the device requires substantial reload time before it can be used again
Solution Approach 1:
The system performs preliminary actions by monitoring activity data from the mobile device and switching to power-saving mode before the user actually stops using the computer. This early detection allows the system to begin power-saving operations in advance, reducing both power consumption and reload time when the user returns.
Solution Approach 2:
The system dynamically adjusts power modes based on real-time activity data from the mobile device. Instead of using fixed timeout periods, the system continuously monitors user behavior patterns and adapts its power state accordingly, switching between normal and power-saving modes as needed.
2Productivity
If the computing device operates at full power to be ready for immediate use, then responsiveness is improved, but unnecessary power is consumed when the device is not being used
Solution Approach 1:
The system uses feedback from activity data monitored via network circuitry to determine when to transition between power modes. By continuously receiving and analyzing activity data from the mobile device, the system can accurately detect user intent and adjust power consumption accordingly, maintaining responsiveness only when needed.
Solution Approach 2:
The system serves itself by automatically detecting user intent through activity data and making independent decisions about power mode transitions. The computing device monitors its own usage patterns via the mobile device's activity data and autonomously adjusts its power state without requiring user intervention or fixed timeout settings.
Data Source
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AI summary
A method is disclosed for performing actions in a computing device based on sensor data from remote devices. While in a power-savings mode, the computing device monitors for activity associated with a mobile device. Based on the monitoring for activity data, the computing device receives an indication that a user of the mobile device intends to use the computing device. Based on the indication, the computing device switches from the power-saving mode to a warming mode, the warming mode comprising restoring power to the one or more components and initiating loading the operational state of the computing device before the user physically interacts with the computing device