Compressive Sampling for Vibration-Based Presence Detection
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Solution Overview
Problem
Conventional signal processing methods for presence detection, such as those using vibration sensors, often require sampling at or above the Nyquist rate to ensure accurate reconstruction of the signal, leading to high power consumption and reduced battery life in mobile devices.
Innovation Solution
The method involves performing compressive sampling of the signal from a vibration sensor by combining data points with a compressive sampling matrix, allowing for the detection of human presence at a sub-Nyquist rate while preserving the relevant signal patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sampling is performed at or above the Nyquist rate to ensure accurate signal reconstruction, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent changes the sampling rate parameter from Nyquist rate or higher to sub-Nyquist rate, enabling lower power consumption while maintaining presence detection accuracy through compressive sampling techniques that process fewer samples
Solution Approach 2:
The patent extracts only the essential information needed for presence detection from the vibration signal, rather than processing the complete high-rate signal. Compressive sampling allows extraction of relevant presence indicators from a reduced set of measurements
2Measurement precision
If sampling is performed at or above the Nyquist rate to ensure accurate signal reconstruction, then measurement precision is improved, but duration of action decreases
Solution Approach 1:
The patent changes the sampling rate parameter to sub-Nyquist rate, reducing energy consumption and extending battery life while maintaining presence detection functionality through compressive sampling
Solution Approach 2:
The patent extracts only the necessary presence detection information from vibration signals, processing a reduced set of compressive measurements rather than complete high-rate signals, thereby conserving battery life
Data Source
AI summary
In some aspects, a device may obtain a signal of a vibration sensor. The device may perform compressive sampling of the signal by combining each set of data points, of a plurality of sets of data points of the signal, with a compressive sampling matrix to obtain a plurality of compressive measurements of the signal. The device may determine whether the plurality of compressive measurements are indicative of a person present in a vicinity of the device. The device may cause the device to exit a low-power mode responsive to a determination that the plurality of compressive measurements are indicative of the person present in the vicinity of the device. Numerous other aspects are described.