Context-Based Power Management for Wearables
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Solution Overview
Problem
Wearable devices face power consumption challenges due to the increasing number and power requirements of input sources needed for advanced context-detection functionality, leading to limited battery life and inefficient power management.
Innovation Solution
Implementing a power management system that classifies input sources into tiers based on power consumption and maintains high-power sources in a lower-power state until a context trigger is detected by a low-power source, transitioning them to a higher-power state only when necessary for context detection and interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-power input sources are kept active continuously to ensure accurate context detection, then detection accuracy is improved, but power consumption increases and battery life decreases
Solution Approach 1:
The system dynamically adjusts the operational state of input sources based on real-time context requirements. Low-power sources remain active while high-power sources are transitioned between sleep and active states according to detected context triggers, optimizing the balance between detection accuracy and power consumption
Solution Approach 2:
High-power input sources are activated periodically or event-driven rather than continuously. The system uses low-power sources to monitor for context triggers, then activates high-power sources only when needed for enhanced detection, creating a periodic activation pattern that reduces overall power consumption
2Adaptability or versatility
If multiple high-power input sources are activated simultaneously for comprehensive context detection, then detection capability is improved, but power consumption increases significantly
Solution Approach 1:
The system segments input sources into distinct power consumption tiers (low-power and high-power sources). This segmentation allows selective activation of only the necessary high-power sources based on specific context requirements, rather than activating all sources simultaneously, thus maintaining detection versatility while controlling power consumption
Solution Approach 2:
Different input sources are assigned different operational qualities based on their power consumption characteristics. Low-power sources operate continuously in a ready state, while high-power sources are activated selectively based on local context needs, ensuring comprehensive detection capability only where and when required
3Duration of action of moving object
If low-power state is maintained for high-power input sources to conserve battery life, then power consumption is reduced, but detection accuracy deteriorates when context detection is needed
Solution Approach 1:
Low-power input sources continuously monitor for context triggers in advance, preparing the system for upcoming high-power source activation. This preliminary detection ensures that when context accuracy is needed, the transition to high-power state occurs promptly, maintaining both battery life and detection accuracy
Solution Approach 2:
The system uses feedback from low-power sources to dynamically control the state of high-power sources. When low-power sources detect specific context patterns or triggers, they provide feedback that activates high-power sources, ensuring accurate context detection only when necessary while preserving battery life during normal operation
Data Source
AI summary
In an embodiment, a computing system causes a computing device to operate in a lower-power state. Data received from a first tier of low-power input source(s) is used to determine user/environmental context and activate a second tier of input source(s) that operate in a higher power range. In each tier the system is running contextual detection to assess whether to engage higher power input sources or sensors to aid the user. With this mechanism, a user is able to have access to a broad range of services without having to explicit switch them on, while the system is able to intelligently manage power and battery life across input sources.