Sensor Mode Switching for False Positive Reduction
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Solution Overview
Problem
The increasing use of sensors in electronic devices leads to higher power consumption, CPU bandwidth usage, and larger device sizes, resulting in increased hardware costs and potential market constraints due to noise and heat dissipation requirements.
Innovation Solution
Implementing a system where an electronic device manages multiple algorithms to process sensor data, including initial and supplemental motion recognition algorithms, which switch between different sensor modes and sensitivity levels to conserve resources, and utilize a memory cache to confirm detected motion and terminate unnecessary algorithms, thereby reducing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors operate in highest signal-to-noise ratio mode continuously, then measurement precision is improved, but use of energy increases and device generates more heat
Solution Approach 1:
The sensor operates dynamically in multiple modes (first mode with lower sensitivity and second mode with higher sensitivity) rather than continuously in highest sensitivity mode. The system switches between modes based on detection needs, allowing high measurement precision only when necessary while conserving energy during normal operation.
Solution Approach 2:
The sensor's operating parameters are changed between different modes. The first mode uses lower sensitivity parameters to conserve energy, while the second mode uses higher sensitivity parameters when motion detection is needed. This parameter switching resolves the contradiction between measurement precision and energy consumption.
2Adaptability or versatility
If multiple sensors and algorithms are used to improve functionality, then adaptability is improved, but device complexity increases
Solution Approach 1:
The motion detection functionality is segmented into multiple algorithms (initial motion recognition algorithm and supplemental motion recognition algorithm) that operate at different levels. The initial algorithm provides quick detection while the supplemental algorithm provides confirmation, dividing the complex task into manageable segments that reduce overall system complexity.
Solution Approach 2:
A memory cache is introduced as an intermediary component to store sensor data. This cache allows algorithms to access historical sensor data without requiring continuous high-power sensor operation, mediating between the sensor and processing algorithms to reduce complexity and power consumption.
3Measurement precision
If sensor data is cached and supplemental algorithms are run to confirm detection, then measurement precision is improved, but use of energy and CPU bandwidth increase
Solution Approach 1:
The system uses itself to verify detections through a two-stage process. The initial motion recognition algorithm performs a quick self-check, and only when motion is detected does the system activate the more resource-intensive supplemental motion recognition algorithm for confirmation. This self-verification approach improves precision while managing power consumption through conditional execution.
Data Source
AI summary
Embodiments are provided for managing the operation of sensors in an electronic device. According to certain aspects, the electronic device may detect a change in motion from a set of lower-sensitivity sensor data generated by a sensor(s) operating in a lower-sensitivity mode. When the change in motion is detected and during a timeout window, the sensor(s) may generate an additional set of lower-sensitivity sensor data and a set of higher-sensitivity sensor data. The electronic device may initially confirm the change in motion based on analyzing the set of higher-sensitivity sensor data. Further, the electronic device may determine that the additional set of lower-sensitivity does not indicate an additional change in motion, and may deem the confirmation of the change in motion as a false positive.


