Motion Sensor Power Management via Dynamic Sampling
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Solution Overview
Problem
High power consumption and increased processor load due to frequent sampling and processing of motion sensor data at high rates in wireless communication devices, which hampers resource availability for other operations.
Innovation Solution
Offloading integration of motion sensor data to processing devices at a lower rate, and managing the operating state of gyroscopes to reduce power consumption by deactivating them when not in use, utilizing more power-efficient sensors like magnetometers for rotation measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion sensor data is sampled and processed at a high rate (e.g., 100 Hz), then measurement precision and responsiveness are improved, but power consumption and processor load increase
Solution Approach 1:
The patent implements periodic sampling of motion sensor data at different rates. High-rate sampling (e.g., 100 Hz) is used when motion is detected or during critical periods, while low-rate sampling (e.g., 1 Hz) is used during stationary periods. This periodic variation in sampling rate maintains measurement precision when needed while significantly reducing power consumption during stable conditions.
Solution Approach 2:
The system dynamically adjusts the sampling rate based on the detected motion state. When motion is detected, the sampling rate increases to capture accurate motion data. When no motion is detected, the sampling rate decreases to conserve power. This dynamic adaptation resolves the contradiction between maintaining high measurement precision and reducing power consumption.
2Measurement precision
If motion sensor data is sampled and processed at a high rate, then measurement precision is improved, but device complexity and resource availability worsen
Solution Approach 1:
The patent implements periodic sampling of motion sensor data at different rates. High-rate sampling (e.g., 100 Hz) is used when motion is detected or during critical periods, while low-rate sampling (e.g., 1 Hz) is used during stationary periods. This periodic variation in sampling rate maintains measurement precision when needed while significantly reducing power consumption during stable conditions.
Solution Approach 2:
The system dynamically adjusts the sampling rate based on the detected motion state. When motion is detected, the sampling rate increases to capture accurate motion data. When no motion is detected, the sampling rate decreases to conserve power. This dynamic adaptation resolves the contradiction between maintaining high measurement precision and reducing power consumption.
3Measurement precision
If gyroscopes are continuously activated for rotation measurements, then measurement precision is improved, but power consumption increases
Solution Approach 1:
The patent implements periodic sampling of motion sensor data at different rates. High-rate sampling (e.g., 100 Hz) is used when motion is detected or during critical periods, while low-rate sampling (e.g., 1 Hz) is used during stationary periods. This periodic variation in sampling rate maintains measurement precision when needed while significantly reducing power consumption during stable conditions.
Solution Approach 2:
The system dynamically adjusts the sampling rate based on the detected motion state. When motion is detected, the sampling rate increases to capture accurate motion data. When no motion is detected, the sampling rate decreases to conserve power. This dynamic adaptation resolves the contradiction between maintaining high measurement precision and reducing power consumption.
Data Source
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AI summary
Systems and methods are described for operating motion sensors in a power-efficient manner. An example technique described herein includes obtaining, at a motion sensor, first indications of sensed motion of a device associated with the motion sensor; integrating, at the motion sensor, the first indications of the sensed motion to obtain integrated motion information; generating, at the motion sensor, second indications of the integrated motion information; and sampling, at a processor disparate from the motion sensor, selective ones of the second indications. Another example technique includes obtaining a first indication of a motion state anomaly associated with motion of a mobile device and causing a gyroscope associated with the mobile device to transition between a first operating mode and a second operating mode in response to the first indication, where the first operating mode is a reduced-power mode compared to the second operating mode.