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Research on the Multiple Factors Influencing Human Identification Based on Pyroelectric Infrared Sensors.

Junwei Yan1, Ping Lou2, Ruiya Li3

  • 1School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China. junweiyan@whut.edu.cn.

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Summary

This study analyzes factors influencing human identification using pyroelectric infrared (PIR) technology. Mathematical models were developed and validated, improving the ability to discriminate human targets by analyzing thermal infrared signals.

Keywords:
identificationmacro-factormapping modelmicro-factorpyroelectric infrared (PIR) sensor

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Area of Science:

  • Biomedical Engineering
  • Sensor Technology
  • Infrared Physics

Background:

  • Human identification using thermal infrared signals is complex.
  • Pyroelectric infrared (PIR) technology offers a non-contact sensing method.
  • Understanding influencing factors is crucial for accurate identification.

Purpose of the Study:

  • To analyze factors affecting human identification via PIR technology.
  • To reveal the mechanism influencing human thermal infrared signal detection.
  • To establish a mapping relationship between sensed waveforms and influencing factors.

Main Methods:

  • Examination of pyroelectric waveforms from human thermal infrared signals.
  • Identification of key influencing factors: distance, target characteristics, PIR sensor, body type, velocity, modulation mask, and Fresnel lens.
  • Development of mathematical models integrating macro and micro factors.

Main Results:

  • Macro-factors indirectly influence human recognition ability in PIR technology.
  • Established mapping relationships and validated mathematical models.
  • Demonstrated improved discrimination of human targets through enhanced PIR data acquisition.

Conclusions:

  • The developed mathematical models accurately describe the relationship between sensed waveforms and influencing factors.
  • The findings enhance the understanding and application of PIR technology for human identification.
  • This research facilitates more effective discrimination of human targets using pyroelectric infrared information.