Human Position Detection with Segmented Pyroelectric Sensor Arrays
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Solution Overview
Problem
Conventional human body position detection methods using pyroelectric sensors suffer from limited measurement range, inaccurate detection due to sensor overlap, and false determinations based solely on temperature measurements.
Innovation Solution
A method and apparatus utilizing an array of three pyroelectric sensors with a Fresnel lens, forming independent detection areas, and determining human presence by analyzing temperature distribution and movement, reducing false positives through width difference thresholds and minimum body width checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple arrayed pyroelectric sensors are used to expand detection range, then the detection range is widened, but the measurement precision deteriorates due to overlap between detection areas
Solution Approach 1:
The detection area is divided into multiple independent sections (first detection area, second detection area, third detection area, etc.) with clear boundaries. Each pyroelectric sensor is assigned to a specific section, eliminating overlap between detection areas. This segmentation allows multiple sensors to work simultaneously without interfering with each other's measurements, thus maintaining high position detection accuracy while expanding the overall detection range.
2Device complexity
If only temperature data is used for human body position detection, then the detection process is simple, but the reliability deteriorates due to false determinations
Solution Approach 1:
The system combines multiple detection parameters - temperature data and width data - to determine human body position. Instead of relying solely on temperature, the system calculates the width of temperature distribution sections and uses both temperature and width information together. This multi-parameter approach significantly reduces false determinations caused by temperature fluctuations from non-human sources, thereby improving detection reliability while maintaining reasonable system complexity.
3Measurement precision
If a single pyroelectric sensor is used, then the measurement precision is high, but the detection range is limited
Solution Approach 1:
The system transitions from a single-point detection approach to a multi-sectional detection approach by dividing the detection area into multiple sections along the detection axis. Each sensor monitors a specific section, creating a one-dimensional array of detection zones. This dimensional expansion allows the system to maintain high measurement precision within each section while achieving a much wider overall detection range through the combination of multiple sections.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances detection accuracy and reliability by integrating movement analysis with temperature data, providing a wide detection range and reducing false detections in complex environments.
Implementation Method 1
a pyroelectric sensor, configured to collect temperature data of a detection area
Implementation Method 2
A Fresnel lens is added to the front end of the apparatus of the present disclosure to enhance the signals
Data Source
Figure 1
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AI summary
A human body position detection method, system and apparatus, and a smart home device. The method comprises: scanning and collecting temperature data of a detection area by using a pyroelectric sensor; selecting the temperature data that is greater than or equal to a minimum temperature threshold and smaller than or equal to a maximum temperature threshold, and connecting the selected temperature data to draw a temperature distribution profile and form n sections; after an interval of time t, scanning and collecting temperature data of the detection area again, selecting the temperature data that is greater than or equal to the minimum temperature threshold and smaller than or equal to the maximum temperature threshold, and connecting the selected temperature data to draw a temperature distribution profile and form n sections; and calculating width differences between the corresponding sections of the temperature data of the two detections, and if a difference is greater than or equal to a width difference threshold, determining that the corresponding section is a person presence section. According to the solution, the determination of whether a person is present is limited not only according to the temperature but also according to whether a target object moves, thereby reducing false determination caused by non-human body heat generation.