Wearable Sensor Sampling Rate Adaptation for Power Management
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Solution Overview
Problem
Current wearable devices do not effectively monitor and adjust power consumption to ensure battery life until a scheduled recharge time, leading to potential battery exhaustion before scheduled charging.
Innovation Solution
A system and method that dynamically adjust the sampling rate of sensors based on contextual requirements and user settings to conserve battery life, using a processor to communicate with sensors and adjust sampling frequencies according to changes in sensor data, ensuring the battery lasts until the next charging time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor sampling frequency is increased to improve activity detection accuracy, then measurement precision is improved, but power consumption increases
Solution Approach 1:
The patent applies dynamics by making the sensor sampling frequency adjustable and adaptive rather than fixed. The system dynamically changes the sampling rate based on detected activity levels - using higher sampling rates during active periods for accurate detection and lower rates during inactive periods to conserve power, thus resolving the contradiction between measurement precision and power consumption
Solution Approach 2:
The patent changes the sampling frequency parameter based on activity detection results. When activity is detected, the system increases the sampling rate to improve measurement precision; when no activity is detected, it decreases the sampling rate to reduce power consumption. This parameter adjustment strategy resolves the technical contradiction by adapting the sampling rate to actual needs
2Reliability
If sensor sampling frequency is maintained at high level to ensure continuous monitoring, then reliability is improved, but battery life deteriorates
Solution Approach 1:
The patent implements periodic action by using activity detection triggers to activate high-frequency sampling only when needed. The system periodically checks for activity and adjusts sampling frequency accordingly - maintaining high sampling rates during activity periods to ensure reliability, and switching to low sampling rates during inactive periods to extend battery life
Solution Approach 2:
The system dynamically adapts the sampling frequency based on activity state, ensuring reliable monitoring during active periods while conserving battery power during inactive periods. This dynamic adjustment resolves the contradiction between maintaining continuous monitoring reliability and extending battery operational duration
3Use of energy by moving object
If sensor sampling frequency is reduced to conserve power, then power consumption is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent changes the sampling frequency parameter based on activity detection - using low sampling rates during inactive periods to reduce power consumption and switching to high sampling rates when activity is detected to maintain measurement precision. This conditional parameter change resolves the contradiction by applying different sampling strategies to different operational states
4Productivity
If processor continuously monitors sensor data at high frequency to ensure accurate activity recognition, then productivity is improved, but power consumption increases
Solution Approach 1:
The patent uses periodic activity detection to trigger processor intervention. Instead of continuously processing sensor data at high frequency, the system periodically checks for activity and activates the processor only when activity is detected, thus improving productivity when needed while reducing power consumption during inactive periods
Solution Approach 2:
The system dynamically adjusts processor activity and sampling frequency based on detected motion. The processor operates at full capacity during activity periods to maintain fast activity recognition, and reduces operation during inactive periods to conserve power, resolving the contradiction between productivity and power consumption
Data Source
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AI summary
System and a method wherein a wearable device receives sensor data at a wearable device and compares a first value determined from the sensor data with a second value determined from the sensor data to determine a percentage change in the sensor data from the first sample to the second sample. The system and method may also change a sampling frequency of the sensor at the wearable device according to one or more settings that were set by a user of the wearable device. The system and method optimizes power consumption while optimally recording data sensed by one or more sensors at a wearable device.