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Multi-Target PIR Indoor Localization and Tracking System with Artificial Intelligence.

Xuan-Ying Chen1, Chih-Yu Wen2, William A Sethares3

  • 1Department of Electrical Engineering, National Chung Hsing University, Taichung 40227, Taiwan.

Sensors (Basel, Switzerland)
|December 11, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel indoor localization system using pyroelectric infrared (PIR) sensors and deep learning. The PIRILS enhances multi-target tracking accuracy and system applicability for smart environments.

Keywords:
artificial intelligencedata augmentation strategydeep learningmultiple targets localizationnon-wearable systempyroelectric infrared sensors

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Area of Science:

  • Robotics and Automation
  • Sensor Technology
  • Artificial Intelligence

Background:

  • Pyroelectric infrared (PIR) sensors are widely used in smart environments due to their low cost, power consumption, and reliability.
  • Device-free indoor localization systems leverage multiple sensors with overlapping fields of view (FOVs) to overcome limitations of individual PIR sensors.

Purpose of the Study:

  • To introduce the Pyroelectric Infrared Indoor Localization System (PIRILS), integrating deep learning with PIR sensor data.
  • To enhance indoor localization capabilities, particularly for tracking multiple targets.

Main Methods:

  • Developed deep learning algorithms tailored to PIR sensor operational characteristics.
  • Implemented a quantized scheme using an artificial neural network (ANN) for multi-target tracking.
  • Utilized a data augmentation strategy to improve training data diversity for motion tracking.

Main Results:

  • Demonstrated improved positioning accuracy and system stability.
  • Showcased expanded applicability for indoor localization.
  • Successfully tracked multiple targets using the developed PIRILS framework.

Conclusions:

  • PIRILS offers an improved framework for indoor multi-target localization.
  • The integration of deep learning significantly enhances PIR sensor-based localization performance.
  • The system shows promise for advanced smart environment applications.