Predictive Power Management for Computing Devices
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Solution Overview
Problem
Conventional sleep and hybrid sleep modes in computing devices do not account for the location, pace, and direction of travel of a user's mobile device, leading to inefficiencies when waking up the device, as they restart applications and services only after the user returns, which can delay the resumption of work.
Innovation Solution
A predictive power-saving management system that determines the location and pace of a user's mobile device to calculate a distance threshold, allowing the device to awaken and restart programs and services before the user arrives, ensuring they are ready for use upon return.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the computing device enters sleep mode or hybrid sleep mode to save power, then energy consumption is reduced, but the device cannot restart programs and services quickly enough when the user returns
Solution Approach 1:
The system performs preliminary actions by detecting when the user is returning (via mobile device location and pace detection) and proactively restarting programs and services before the user actually arrives at the computing device. This resolves the contradiction by preparing the system in advance, so that when the user returns, the device is already ready to use without delay.
2Productivity
If the computing device restarts programs and services immediately upon user return, then productivity is improved, but energy is wasted if the user returns quickly from a nearby location
Solution Approach 1:
The system dynamically adjusts its behavior based on real-time conditions. It continuously monitors the mobile device's location and calculates the user's pace and time of arrival. The decision to restart programs and services is made dynamically based on whether the user is returning from a remote or nearby location, optimizing both productivity and energy consumption adaptively.
Solution Approach 2:
The system uses feedback from mobile device location data, pace detection, and time calculations to make intelligent decisions about when to restart programs and services. This feedback mechanism allows the system to distinguish between users returning quickly from nearby locations (avoiding unnecessary restarts) and users returning from remote locations (triggering proactive restarts).
Data Source
AI summary
Approaches are provided for a predictive electrical appliance power-saving management mode. An approach includes ascertaining a location and pace of a mobile device. The approach further includes calculating an amount of time that it will take to enable or start programs and services upon a computing device waking from a sleep mode or hybrid sleep mode. The approach further includes determining a distance threshold to the computing device that allows for the calculated amount of time to pass such that the programs and services are enabled or started prior to a user of the mobile device arriving at the computing device when the user is returning to the computing device at the ascertained pace. The approach further includes sending a signal to awaken the computing device from the sleep mode or hybrid sleep mode when the mobile device is within the distance threshold.