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A Distributed Self-adaptive Nonparametric Change-Detection Test for Sensor/Actuator Networks

  • Cesare Alippi
  • Giacomo Boracchi
  • Manuel Roveri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6792)

Abstract

The prompt detection of faults and, more in general, changes in stationarity in networked systems such as sensor/actuator networks is a key issue to guarantee robustness and adaptability in applications working in real-life environments. Traditional change-detection methods aiming at assessing the stationarity of a data generating process would require a centralized availability of all observations, solution clearly unacceptable when large scale networks are considered and data have local interest. Differently, distributed solutions based on decentralized change-detection tests exploiting information at the unit and cluster level would be a solution. This work suggests a novel distributed change-detection test which operates at two-levels: the first, running on the unit, is particularly reactive in detecting small changes in the process generating the data, whereas the second exploits distributed information at the cluster-level to reduce false positives. Results can be immediately integrated in the machine learning community where adaptive solutions are envisaged to address changes in stationarity of the considered application. A large experimental campaign shows the effectiveness of the approach both on synthetic and real data applications.

Keywords

Change detection test sensor/actuator networks fault detection 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Cesare Alippi
    • 1
  • Giacomo Boracchi
    • 1
  • Manuel Roveri
    • 1
  1. 1.Dipartimento di Elettronica e InformazionePolitecnico di MilanoMilanoItaly

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