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A Self-Localization Algorithm for Mobile Targets in Indoor Wireless Sensor Networks Using Wake-Up Media Access

Rihab Souissi1,2,3, Salwa Sahnoun2,3, Mohamed Khalil Baazaoui1,2,3

  • 1Smart Diagnostic and Online Monitoring, Leipzig University of Applied Sciences, Wächterstraße 13, 04107 Leipzig, Germany.

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Summary
This summary is machine-generated.

This study presents a novel self-localization algorithm for mobile targets in wireless sensor networks (WSN). The wake-up media access control (MAC) protocol and trilateration with RSSI measurements significantly reduce energy consumption and improve indoor localization accuracy.

Keywords:
OMNeT++indoor localizationlow-energy consumptionreceived signal strength indicationwake-up receiverwireless sensor network

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Area of Science:

  • Wireless Sensor Networks (WSN)
  • Indoor Localization
  • Mobile Target Tracking

Background:

  • Indoor localization in WSNs faces challenges like interference, obstacles, and high energy consumption.
  • Existing systems struggle with latency, power demands, and accuracy, necessitating battery replacements.
  • Accurate and energy-efficient mobile localization is crucial for numerous WSN applications.

Purpose of the Study:

  • To introduce an innovative self-localization algorithm for mobile targets in WSNs.
  • To address critical challenges of latency, energy consumption, and accuracy in indoor tracking.
  • To optimize overall energy consumption for mobile localization applications.

Main Methods:

  • Developed a novel self-localization algorithm utilizing the wake-up media access control (MAC) protocol.
  • Employed the trilateration technique combined with Received Signal Strength Indication (RSSI) measurements.
  • Implemented simulations using the OMNeT++ discrete event simulator and C++ programming language, incorporating real indoor RSSI measurements and an optimal parameter determination approach.

Main Results:

  • Achieved significant reduction in power consumption, utilizing only 2.69% for localizing 100 positions.
  • Demonstrated exceptional accuracy with an average error of 1.91 m in 90% of cases.
  • Validated the effectiveness of the wake-up MAC protocol and RSSI-based trilateration for energy-efficient indoor localization.

Conclusions:

  • The proposed self-localization algorithm offers an innovative and efficient solution for mobile target tracking in WSNs.
  • The system effectively balances accuracy and energy consumption, outperforming existing methods.
  • This approach significantly optimizes energy usage, making it suitable for battery-powered WSN devices.