A-Posteriori Detection of Sensor Infrastructure Errors in Correlated Sensor Data and Business Workflows

  • Andreas Wombacher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6896)


Some physical objects are influenced by business workflows and are observed by sensors. Since both sensor infrastructures and business workflows must deal with imprecise information, the correlation of sensor data and business workflow data related to physical objects might be used a-posteriori to determine the source of the imprecision. In this paper, an information theory based approach is presented to distinguish sensor infrastructure errors from inhomogeneous business workflows. This approach can be applied on detecting imprecisions in the sensor infrastructure, like e.g. sensor errors or changes of the sensor infrastructure deployment.


Mutual Information Sensor Data Physical Object Sensor Reading Digital Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Andreas Wombacher
    • 1
  1. 1.Database GroupUniversity of TwenteThe Netherlands

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