---
_id: '2007'
abstract:
- lang: eng
  text: Multisensor systems are susceptible to sensor ageing effects as well as to
    environmental changes. Due to these effects, the distribution of sensor measurements
    may change over time, which is referred to as sensor drift. A multisensor system
    which adapts to drift by self-monitoring is more durable, requires less manual
    maintenance, and provides information of higher quality. This contribution proposes
    an approach for detecting and adapting to sensor drift. The proposed detection
    algorithm determines the reliability of a sensor based on fuzzy pattern classifiers
    and a consistency measure. By this means, the inherent redundancy in multisensor
    systems is exploited to detect drift. Detected drift leads then to a retraining
    of the classifier on batched data guided by information fusion. The retraining
    incorporates the estimated magnitude of the drift. The proposed algorithms are
    evaluated in comparison with state-of-the-art methods in the scope of a publicly
    available dataset. It is shown that the drift detection algorithm yields results
    similar to the benchmark algorithm but is less computationally complex. Relearning
    with the drift-adapted approach results in more robust classifiers with regard
    to potential future drift.
author:
- first_name: Christoph-Alexander
  full_name: Holst, Christoph-Alexander
  id: '64782'
  last_name: Holst
- first_name: Volker
  full_name: Lohweg, Volker
  id: '1804'
  last_name: Lohweg
  orcid: 0000-0002-3325-7887
citation:
  ama: 'Holst C-A, Lohweg V. A Conflict-Based Drift Detection And Adaptation Approach
    for Multisensor Information Fusion. In: <i>23rd IEEE International Conference
    on Emerging Technologies and Factory Automation (ETFA)</i>. Torino, Italy; 2018.
    doi:<a href="https://doi.org/10.1109/ETFA.2018.8502571">10.1109/ETFA.2018.8502571</a>'
  apa: Holst, C.-A., &#38; Lohweg, V. (2018). A Conflict-Based Drift Detection And
    Adaptation Approach for Multisensor Information Fusion. In <i>23rd IEEE International
    Conference on Emerging Technologies and Factory Automation (ETFA)</i>. Torino,
    Italy. <a href="https://doi.org/10.1109/ETFA.2018.8502571">https://doi.org/10.1109/ETFA.2018.8502571</a>
  bjps: <b>Holst C-A and Lohweg V</b> (2018) A Conflict-Based Drift Detection And
    Adaptation Approach for Multisensor Information Fusion. <i>23rd IEEE International
    Conference on Emerging Technologies and Factory Automation (ETFA)</i>. Torino,
    Italy.
  chicago: Holst, Christoph-Alexander, and Volker Lohweg. “A Conflict-Based Drift
    Detection And Adaptation Approach for Multisensor Information Fusion.” In <i>23rd
    IEEE International Conference on Emerging Technologies and Factory Automation
    (ETFA)</i>. Torino, Italy, 2018. <a href="https://doi.org/10.1109/ETFA.2018.8502571">https://doi.org/10.1109/ETFA.2018.8502571</a>.
  chicago-de: 'Holst, Christoph-Alexander und Volker Lohweg. 2018. A Conflict-Based
    Drift Detection And Adaptation Approach for Multisensor Information Fusion. In:
    <i>23rd IEEE International Conference on Emerging Technologies and Factory Automation
    (ETFA)</i>. Torino, Italy. doi:<a href="https://doi.org/10.1109/ETFA.2018.8502571,">10.1109/ETFA.2018.8502571,</a>
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Holst, Christoph-Alexander</span>
    ; <span style="font-variant:small-caps;">Lohweg, Volker</span>: A Conflict-Based
    Drift Detection And Adaptation Approach for Multisensor Information Fusion. In:
    <i>23rd IEEE International Conference on Emerging Technologies and Factory Automation
    (ETFA)</i>. Torino, Italy, 2018'
  havard: 'C.-A. Holst, V. Lohweg, A Conflict-Based Drift Detection And Adaptation
    Approach for Multisensor Information Fusion, in: 23rd IEEE International Conference
    on Emerging Technologies and Factory Automation (ETFA), Torino, Italy, 2018.'
  ieee: C.-A. Holst and V. Lohweg, “A Conflict-Based Drift Detection And Adaptation
    Approach for Multisensor Information Fusion,” in <i>23rd IEEE International Conference
    on Emerging Technologies and Factory Automation (ETFA)</i>, Torino, Italy, 2018.
  mla: Holst, Christoph-Alexander, and Volker Lohweg. “A Conflict-Based Drift Detection
    And Adaptation Approach for Multisensor Information Fusion.” <i>23rd IEEE International
    Conference on Emerging Technologies and Factory Automation (ETFA)</i>, 2018, doi:<a
    href="https://doi.org/10.1109/ETFA.2018.8502571">10.1109/ETFA.2018.8502571</a>.
  short: 'C.-A. Holst, V. Lohweg, in: 23rd IEEE International Conference on Emerging
    Technologies and Factory Automation (ETFA), Torino, Italy, 2018.'
  ufg: '<b>Holst, Christoph-Alexander/Lohweg, Volker (2018)</b>: A Conflict-Based
    Drift Detection And Adaptation Approach for Multisensor Information Fusion, in:
    <i>23rd IEEE International Conference on Emerging Technologies and Factory Automation
    (ETFA)</i>, Torino, Italy.'
  van: 'Holst C-A, Lohweg V. A Conflict-Based Drift Detection And Adaptation Approach
    for Multisensor Information Fusion. In: 23rd IEEE International Conference on
    Emerging Technologies and Factory Automation (ETFA). Torino, Italy; 2018.'
conference:
  end_date: 2018-09-07
  location: Torino, Italy
  name: IEEE 23rd International Conference on Emerging Technologies and Factory Automation
    (ETFA) 2018
  start_date: 2018-09-04
date_created: 2019-11-25T08:35:47Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
doi: 10.1109/ETFA.2018.8502571
keyword:
- Multisensor systems
- Temperature measurement
- Current measurement
- Redundancy
- Pollution measurement
- Detection algorithms
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/abstract/document/8502571
place: Torino, Italy
publication: 23rd IEEE International Conference on Emerging Technologies and Factory
  Automation (ETFA)
publication_status: published
status: public
title: A Conflict-Based Drift Detection And Adaptation Approach for Multisensor Information
  Fusion
type: conference
user_id: '15514'
year: 2018
...