Computing Device Sleep State Adjustment via Proximity Detection
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Solution Overview
Problem
Conventional computing devices take a long time to re-enter a fully-functional state due to the time-consuming process of powering on internal components from sleep states, causing user inconvenience and inefficiency in energy usage.
Innovation Solution
The techniques involve adjusting sleep states based on proximity detection and historical user behavior, using methods such as detecting remote devices and scheduling deep and light sleep signals to optimize power usage and reduce startup times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the system increasingly lowers or switches off power to internal components after sleep time elapses, then energy efficiency is improved, but the time required to re-enter a fully-functional state increases
Solution Approach 1:
The patent implements multiple dynamic sleep states (first sleep state, second sleep state, third sleep state) with progressively deeper power reduction. The system can transition between these states based on inactivity duration and user proximity detection, allowing it to adapt between energy efficiency and quick reactivation needs. When a portable device is detected nearby, the system transitions to lighter sleep states that enable faster wake-up while still conserving energy during extended inactivity.
Solution Approach 2:
The system changes operational parameters by adjusting power levels to internal components across different sleep states. By modifying power supply parameters dynamically based on sleep duration and proximity detection, the system optimizes the trade-off between energy consumption and reactivation time, selecting appropriate power reduction levels for current usage patterns.
2Loss of energy
If the system enters a low-power sleep state to conserve energy, then power consumption is reduced, but the system requires considerable time to re-animate components when abruptly required to wake
Solution Approach 1:
The system performs preliminary actions by detecting the proximity of portable devices (smartphones, tablets, wearables) before the user actually needs to use the computing device. When such devices are detected nearby, the system anticipates upcoming user activity and transitions to lighter sleep states or maintains higher power levels, preparing components in advance for quick activation without wasting energy during confirmed inactivity periods.
Solution Approach 2:
The system uses feedback from proximity detection mechanisms to continuously monitor and adjust sleep states. By receiving feedback about nearby portable devices, the system dynamically modifies its power management strategy, balancing energy conservation during true inactivity with quick responsiveness when user presence is detected, thereby optimizing both power consumption and system responsiveness.
3Use of energy by moving object
If the system transitions between multiple sleep states based on duration, then energy efficiency is optimized, but device complexity increases
Solution Approach 1:
The proximity detection mechanism serves multiple functions: it detects user presence, triggers sleep state transitions, and provides contextual information for power management decisions. By making the detection system multi-functional, the patent reduces the need for separate specialized components, thereby managing device complexity while enabling sophisticated energy optimization across multiple sleep states.
Data Source
AI summary
This application relates to techniques that adjust the sleep states of a computing device based on proximity detection and predicted user activity. Proximity detection procedures can be used to determine a proximity between the computing device and a remote computing device coupled to the user. Based on these proximity detection procedures, the computing device can either correspondingly increase or decrease the amount power supplied to the various components during either a low-power sleep state or a high-power sleep state. Additionally, historical user activity data gathered on the computing device can be used to predict when the user will likely use the computing device. Based on the gathered historical user activity, deep sleep signals and light sleep signals can be issued at a time when the computing device is placed within a sleep state which can cause it to enter either a low-power sleep state or a high-power sleep state.