Anomaly Behavior Analysis for Sensors Fault Detection

Guillermo Perez, Jesus Pacheco, Victor Benitez

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

Abstract

In today's world, sensors play a crucial role, as they feed information to make accurate decisions and take actions; therefore, making sure that sensors behave correctly is critical. In this work, we focus on inspecting the data provided by sensors, aiming at discovering any issue due to malfunction, misuse, or any other source of error before the issue is propagated through the system. To achieve that, we propose a novel approach based on wavelets embedded in a microcontroller to analyze data from sensors. The objective is to determine whether the sensor is issuing correct data (normal behavior) or not (abnormal behavior), to prevent the error from reaching other parts of the system.

Original languageEnglish
Title of host publication2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1718-1723
Number of pages6
ISBN (Electronic)9781665430654
DOIs
StatePublished - 2023
Event2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 - Mexico City, Mexico
Duration: 5 Dec 20238 Dec 2023

Publication series

Name2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

Conference

Conference2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
Country/TerritoryMexico
CityMexico City
Period5/12/238/12/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Embedded Systems
  • Euclidean distance
  • anomaly behavior analysis
  • discrete wavelet transform
  • sensor's fault detection

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