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Tag Localization with Asynchronous Inertial-Based Shifting and Trilateration.

Abdallah Y Alma'aitah1, Lobna M Eslim2, Hossam S Hassanein2

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Summary
This summary is machine-generated.

This study introduces a cooperative crowdsourcing scheme for localizing mobile low-power tags in the Internet of Things (IoT). The Inertial-Based Shifting and Trilateration (IBST) technique accurately estimates tag locations, even with limited reader coverage.

Keywords:
RSSIcrowdsourcinginertial sensorlocalization

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Robotics

Background:

  • Personal Area Networks (PAN) are crucial for Internet of Things (IoT) localization.
  • Existing localization methods often assume centralized control and synchronization.
  • Crowdsourcing offers a decentralized approach to enhance localization accuracy.

Purpose of the Study:

  • To propose a cooperative crowdsourcing scheme for localizing mobile low-power tags.
  • To introduce the Inertial-Based Shifting and Trilateration (IBST) technique for accurate tag localization.
  • To enable localization in both GPS-assisted outdoor and indoor environments.

Main Methods:

  • Leveraging crowdsourcing from fixed and mobile readers.
  • Implementing a cooperative scheme for distributed and mobile/fixed readers.
  • Utilizing the Inertial-Based Shifting and Trilateration (IBST) technique for location estimation.

Main Results:

  • IBST accurately estimates the absolute location of mobile tags.
  • The technique provides location estimates even with fewer than three readers.
  • IBST demonstrates scalability with no processing required by low-power tags.

Conclusions:

  • IBST offers a robust and scalable solution for mobile tag localization in IoT.
  • The proposed method overcomes limitations of state-of-the-art techniques requiring simultaneous data.
  • IBST enhances localization accuracy and reliability in diverse environments.