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Summary
This summary is machine-generated.

This study introduces the Force Estimation and Event Localization (FEEL) algorithm for accurate indoor person localization using footsteps. FEEL achieves 98.6% accuracy, overcoming privacy and device limitations of other methods.

Keywords:
Body–weight ratioFEELFootstepsForce estimationLocalizationStructural vibrations

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Area of Science:

  • Smart Environments
  • Human-Computer Interaction
  • Sensor Fusion

Background:

  • Indoor localization is crucial for smart environments but faces challenges like privacy concerns and device requirements.
  • Existing methods often rely on time-of-flight variations, necessitating complex infrastructure or wearable devices.
  • Structural vibrations from footsteps offer a privacy-preserving, device-free alternative for indoor positioning.

Purpose of the Study:

  • To present the Force Estimation and Event Localization (FEEL) algorithm for improved indoor person localization.
  • To demonstrate FEEL's effectiveness using lower sampling rates and fewer sensors compared to time-of-flight methods.
  • To enhance FEEL's force estimation and localization accuracy for practical applications.

Main Methods:

  • Developed and improved the Force Estimation and Event Localization (FEEL) algorithm.
  • Utilized structural vibrations generated by footsteps for localization.
  • Analyzed 1100 footsteps to evaluate localization accuracy and estimate ground force reactions (GRF).

Main Results:

  • Achieved 98.6% localization accuracy with the improved FEEL algorithm.
  • FEEL demonstrated superior performance with lower sampling rates and fewer sensors.
  • Accurately estimated participant body-weight-ratios (BWR) from ground force reactions.

Conclusions:

  • The improved FEEL algorithm offers a highly accurate and practical solution for indoor person localization.
  • FEEL effectively overcomes privacy and device-related challenges associated with other localization technologies.
  • The algorithm's ability to estimate body-weight-ratios adds further utility for smart environment applications.