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Combined Methods Based Outlier Detection for Water Pipeline in Wireless Sensor Networks

  • Oussama GhorbelEmail author
  • Aya Ayadi
  • Rami Ayadi
  • Mohammed Aseeri
  • Mohamed Abid
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 926)

Abstract

In the last years, Wireless Sensor Networks (WSNs) has become a very interesting field for researchers. They are widely employed to solve several problems in different domains like agriculture, monitoring, health care. Then, outlier detection method is considered as a very important step in construction of sensor network systems to ensure data grade for perfect decision making. So, this task helps to create a gainful approach to find out if data is normal regular or an outlier. Therefore, in this paper, a newest outlier’s detection and classification model has been developed to complement the existing hardware redundancy and limit checking techniques. To overcome these problems, we present a Combined Outliers Detection Method (CODM) for water pipeline to detect damaged data in WSNs. To this end, the application of kernel-based non-linear approach is introduced. The main objective of this work was to combine the advantages of Kernel Fisher Discriminant Analysis (KFDA) and Support Vector Machine (SVM) to enhance the performance of the monitoring water pipeline system. The accuracy of our Combined Outliers Detection Method for classification was analyzed and compared with variety of methods. Finally, based on the experimental results, our proposed work shows a better performance to detecting outliers in the monitoring water pipeline process.

Keywords

Outlier detection method Wireless Sensor Networks (WSNs) Monitoring water pipeline Kernelized techniques 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Oussama Ghorbel
    • 1
    • 2
    • 4
    Email author
  • Aya Ayadi
    • 1
  • Rami Ayadi
    • 2
  • Mohammed Aseeri
    • 3
  • Mohamed Abid
    • 1
    • 4
  1. 1.National Engineers School of SfaxSfax University, CES-LabSfaxTunisia
  2. 2.Jouf UniversitySakakahKingdom of Saudi Arabia
  3. 3.King Abdulaziz City for Science and Technology (KACST)RiyadhKingdom of Saudi Arabia
  4. 4.Digital Research Center of SfaxSfaxTunisia

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