• DocumentCode
    316253
  • Title

    Data representation and organization for an industrial multisensor integration architecture

  • Author

    Naish, Michael D. ; Croft, Elizabeth A.

  • Author_Institution
    Dept. of Mech. Eng., British Columbia Univ., Vancouver, BC, Canada
  • Volume
    1
  • fYear
    1997
  • fDate
    12-15 Oct 1997
  • Firstpage
    821
  • Abstract
    An open architecture for intelligent multisensor integration in an industrial environment is being developed. A logical sensor model is used to represent both real and abstract sensors within the architecture, allowing for the ready addition or replacement of sensors. Processing algorithms are also encapsulated by logical sensors. Objects are modeled using a connected graph structure wherein each node represents a salient feature of the object. Interactive training is used to determine the logical sensors required to extract desired features from objects. Extracted features are identified by the user and become part of the model. Once trained, the system can use object models for identification and classification purposes
  • Keywords
    automatic optical inspection; process control; sensor fusion; classification; connected graph structure; data organization; data representation; feature extraction; industrial environment; industrial multisensor integration architecture; intelligent multisensor integration; interactive training; logical sensor model; open architecture; Computer architecture; Computer industry; Data mining; Feature extraction; Food industry; Inspection; Intelligent sensors; Machinery production industries; Mechanical sensors; Sensor systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-4053-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1997.626200
  • Filename
    626200