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SCALING: plug-n-play device-free indoor tracking.

Zongxing Xie1, Fan Ye2

  • 1Electrical and Computer Engineering Department, Stony Brook University, Stony Brook, 11794, USA. zongxing.xie@stonybrook.edu.

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|February 5, 2024
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Summary

SCALING offers easy, device-free indoor tracking for health monitoring. Its self-calibrating system requires minimal user effort, making home health assessments more accessible.

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Area of Science:

  • Computer Science
  • Ubiquitous Computing
  • Health Informatics

Background:

  • Continuous in-home monitoring of daily trajectories aids health status assessment, particularly for conditions like Alzheimer's and dementia.
  • Device-free indoor localization and tracking are ideal for unobtrusive health monitoring, eliminating the need for wearable devices.
  • Previous localization methods required extensive manual sensor calibration, limiting scalability and user accessibility.

Purpose of the Study:

  • To introduce SCALING, a plug-and-play indoor trajectory monitoring system designed for easy setup by non-expert users.
  • To enable scalable, device-free, continuous in-home health monitoring through self-calibrating radar technology.
  • To reduce the significant manual effort and expertise typically required for sensor calibration in indoor localization systems.

Main Methods:

  • SCALING employs a self-calibrating algorithm that estimates sensor locations based on distance measurements to a user walking a short loop trajectory.
  • The system utilizes radar nodes placed on walls, requiring only a one-minute user walk for initial calibration.
  • Evaluation involved simulations and two testbeds (lab and home) with varying configurations.

Main Results:

  • SCALING demonstrated superior performance over approximate multidimensional scaling (MDS) by 3.5 m and 1.6 m in 80-percentile error for self-calibration and tracking, respectively.
  • The system achieved performance degradation of only 1% compared to classical multilateration with pre-calibrated sensor locations.
  • Monte Carlo experiments provided insights into sensor placement impact and practical deployment guidelines.

Conclusions:

  • SCALING significantly reduces the setup burden for indoor trajectory monitoring, making it feasible for widespread home use.
  • The system offers a practical and scalable solution for continuous, device-free health monitoring, supporting early detection and management of neurological conditions.
  • The self-calibrating approach democratizes indoor localization technology, enabling non-experts to deploy and utilize sophisticated health monitoring systems.