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Related Experiment Video

Updated: Jul 10, 2026

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

Target source detection using an improved sensing model in wireless sensor networks (ISMWSNs).

Yongju Yang1, Junghoon Lee, Jipmin Jung

  • 1Department of Biomedical Engineering, Graduated School of Yonsei University, Gangwon-do, Korea. yyjo498@hanmail.net

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 16, 2007
PubMed
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We developed a new sensing model and inverse problem approach to accurately locate sources using radio signal strength indicator (RSSI) measurements in sensor networks. This method effectively identifies the original source, distinguishing it from others.

Area of Science:

  • Sensor Networks
  • Signal Processing
  • Inverse Problems

Background:

  • Accurate source localization is crucial in sensor networks.
  • Existing methods may not fully account for signal propagation complexities.

Purpose of the Study:

  • To propose and validate a novel sensing model for calculating Received Signal Strength Indicator (RSSI) between sensors and sources.
  • To apply an inverse problem approach for precise source localization using RSSI measurements.

Main Methods:

  • Developed a new sensing model incorporating source orientation vectors.
  • Utilized a linear inverse problem to determine source location based on calculated RSSI.
  • Simulated the sensing model to evaluate its performance in source detection.

Related Experiment Videos

Last Updated: Jul 10, 2026

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

Main Results:

  • The proposed sensing model accurately calculated RSSI, considering source orientation.
  • The inverse problem approach successfully detected the original source.
  • Simulations confirmed the model's ability to distinguish the true source, with its norm significantly larger than others.

Conclusions:

  • The novel sensing model and inverse problem approach provide an effective method for source localization in sensor networks.
  • The technique demonstrates robustness and accuracy in identifying the intended source within a distributed network.