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A Tagless Indoor Localization System Based on Capacitive Sensing Technology.

Alireza Ramezani Akhmareh1, Mihai Teodor Lazarescu2, Osama Bin Tariq3

  • 1Politecnico di Torino, Corso Duca degli Abruzzi, Torino 24-10129, Italy. alireza.ramezani@polito.it.

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This study presents a tagless indoor person localization system using capacitive sensing, achieving sub-0.2m accuracy. The system enhances assisted living technologies with precise, low-error human tracking.

Keywords:
capacitive sensingindoor localizationtagless localization

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Area of Science:

  • Engineering
  • Computer Science
  • Human-Computer Interaction

Background:

  • Accurate indoor person localization is crucial for applications like assisted living and robotics.
  • Existing systems often rely on wearable tags or complex infrastructure, limiting practicality.

Purpose of the Study:

  • To develop and evaluate a tagless indoor person localization system using capacitive sensing.
  • To assess the system's performance in terms of accuracy, precision, and recall.
  • To investigate noise reduction techniques for improved system robustness and energy efficiency.

Main Methods:

  • Implementation of a capacitive sensing array for human detection and localization.
  • Application and comparison of various standard localization algorithms.
  • Analysis of noise effects and implementation of on-sensor filters for noise reduction.

Main Results:

  • Achieved average localization error below 0.2 m in a 3 m × 3 m room.
  • Demonstrated recall and precision rates exceeding 70%.
  • Identified effective filtering strategies for noise reduction and energy saving.

Conclusions:

  • The proposed tagless capacitive sensing system offers a promising solution for accurate indoor localization.
  • The system's performance is robust to noise, with effective mitigation strategies identified.
  • This technology has significant potential for enhancing services in assisted living and other indoor environments.