Human Motion Sensor Automatic Calibration Method
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Solution Overview
Problem
Existing human motion sensors require time-consuming and complicated manual adjustments for parameters like brightness and sensing distance, which not all users can perform effectively, and once installed, further adjustments are troublesome.
Innovation Solution
An automatic calibration method for human motion sensors with a self-learning function, involving steps to set a default trigger value, sample and judge signals, record and update trigger conditions, and analyze and adjust settings, allowing the sensor to adapt and improve its performance over time without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adjustment of sensor parameters is performed, then the sensor can be configured for specific conditions, but the operation becomes time-consuming and complicated
Solution Approach 1:
The sensor system automatically performs calibration by detecting user presence and absence, eliminating the need for manual parameter adjustment. The control unit autonomously determines optimal sensitivity and timing parameters based on detected motion patterns, allowing the system to calibrate itself without user intervention.
Solution Approach 2:
The system performs preliminary calibration actions automatically during initial setup and subsequent operations. By pre-programming the automatic calibration sequence that detects user presence/absence and adjusts parameters accordingly, the system eliminates the need for users to perform complex manual adjustments later.
2Adaptability or versatility
If manual adjustment of sensor parameters is performed, then the sensor can be configured for specific conditions, but further adjustments become troublesome after installation
Solution Approach 1:
The sensor system dynamically adapts its parameters based on real-time detection of user presence and absence. The control unit continuously monitors motion patterns and automatically adjusts sensitivity and timing parameters, enabling the system to adapt to changing conditions without requiring manual reconfiguration after installation.
Solution Approach 2:
The system incorporates feedback mechanisms where the control unit detects motion signals, analyzes user presence/absence patterns, and uses this feedback to automatically adjust sensor parameters. This closed-loop approach allows the sensor to maintain optimal performance across different installation environments without troublesome post-installation adjustments.
3Adaptability or versatility
If default trigger value includes environment factor noise, then the sensor can operate in various conditions, but the trigger accuracy may be affected
Solution Approach 1:
The system converts environmental noise, which would normally be a harmful interference, into useful calibration data. By intentionally including environment factor noise in the default trigger value and using it during automatic calibration, the system learns to distinguish between noise and actual motion signals, improving both adaptability and accuracy.
Solution Approach 2:
The control unit dynamically changes trigger value parameters based on detected environmental conditions. During automatic calibration, the system adjusts sensitivity and threshold parameters to account for ambient noise levels, maintaining accurate triggering across diverse environmental conditions while filtering out noise interference.
Data Source
AI summary
The present invention discloses an automatic calibration method of a sensor, including the following steps of: (A1) setting a default trigger value; (A2) sampling a signal and accumulating a signal value to perform signal judgment; (A3) determining whether a trigger condition is met or not; (A4) if yes, recording an accumulated signal value meeting the trigger condition, and if not, returning to step (A2); and (A5) analyzing and updating the default trigger value.