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Probabilistic Assessment of High-Throughput Wireless Sensor Networks.

Robin E Kim1, Kirill Mechitov2, Sung-Han Sim3

  • 1Fire Research Center, Korea Institute of Civil Engineering and Building Technology, Gyeonggi-do 18544, Korea. robineunjukim@kict.re.kr.

Sensors (Basel, Switzerland)
|June 4, 2016
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Summary

This study introduces a new probabilistic model to assess wireless smart sensor (WSS) network reliability for structural health monitoring (SHM). The model accurately predicts long-term network performance, ensuring robust data transfer for critical infrastructure assessment.

Keywords:
high-throughput data transfernetwork communication reliabilityprobabilistic assessmentstructural health monitoringwireless sensor networks

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Area of Science:

  • Engineering
  • Computer Science
  • Data Science

Background:

  • Wireless smart sensors (WSS) offer valuable data for structural health monitoring (SHM).
  • Maintaining reliable WSS networks is challenging due to their distributed nature.
  • Existing methods for assessing WSS network reliability are insufficient for high-throughput data transfer required in SHM.

Purpose of the Study:

  • To develop a probabilistic model for assessing the long-term performance of WSS networks in SHM.
  • To provide a method for estimating the probability of network communication failure.
  • To enable optimized sensor topology design for complex WSS networks.

Main Methods:

  • Utilizing readily-available measured data sets of communication quality during high-throughput data transfer.
  • Determining an empirical limit-state function based on measured data.
  • Employing Monte Carlo simulation to estimate network communication failure probability.
  • Applying the model to small and full-bridge wireless networks.

Main Results:

  • The proposed model accurately assesses the probabilistic long-term performance of WSS networks.
  • The method effectively estimates the probability of network communication failure.
  • The analysis facilitated the identification of optimized sensor topologies for tested networks.

Conclusions:

  • The developed probabilistic model is a significant advancement for ensuring reliable WSS networks in SHM.
  • This approach addresses the limitations of previous methods in handling high-throughput data.
  • The findings support the design of more robust and efficient sensor networks for critical infrastructure monitoring.