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Distributed Estimation of Anomalies using a Low Complexity PSO Algorithm

  • Muhammad Omer Bin Saeed
  • , Salman A. Khan
  • , Naveed R. Butt
  • , Nazeeruddin Mohammad
  • , Azzedine Zerguine

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Any wireless sensor network can experience anomalies that can hinder performance. This work presents a distributed estimation algorithm that estimates any such anomalies using a PSO algorithm. PSO algorithms are computationally expensive. This work presents a low complexity version of the algorithm that removes redundant computations and achieves excellent performance as well. Low complexity algorithms are essential for a longer battery life of wireless sensor so this algorithm provides an excellent alternative to the basic linear adaptive filtering algorithms that have low complexity but require a lot more time to achieve similar results.

Original languageEnglish
Title of host publication2024 International Conference on Emerging Trends in Smart Technologies, ICETST 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331515850
DOIs
StatePublished - 2024
Event2024 International Conference on Emerging Trends in Smart Technologies, ICETST 2024 - Karachi, Pakistan
Duration: 10 Oct 202411 Oct 2024

Publication series

Name2024 International Conference on Emerging Trends in Smart Technologies, ICETST 2024

Conference

Conference2024 International Conference on Emerging Trends in Smart Technologies, ICETST 2024
Country/TerritoryPakistan
CityKarachi
Period10/10/2411/10/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • Distributed Estimation
  • Event Triggering
  • Low Complexity
  • Particle Swarm Optimization
  • Self-Organizing Hierarchical PSO

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Control and Optimization

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