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Conference Papers Year : 2013

Building Heterogeneous Models at Runtime to Detect Faults in Ambient-Intelligent Environments

Abstract

This paper introduces an approach for fault detection in ambient-intelligent environments. It proposes to compute predictions for sensor values, to be compared with actual values. As ambient environments are highly dynamic, one cannot pre-determine a prediction method. Therefore, our approach relies on (a) the modeling of sensors, actuators and physical effects that link them, and (b) the automatic construction at run-time of a heterogeneous prediction model. The prediction model can then be executed on a heterogeneous modeling platform such as ModHel'X, which yields predicted sensor values.
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Dates and versions

hal-00905275 , version 1 (18-11-2013)

Identifiers

  • HAL Id : hal-00905275 , version 1

Cite

Christophe Jacquet, Ahmed Mohamed, Frédéric Boulanger, Cécile Hardebolle, Yacine Bellik. Building Heterogeneous Models at Runtime to Detect Faults in Ambient-Intelligent Environments. MRT 2013, Sep 2013, Miami, United States. pp.52-63. ⟨hal-00905275⟩
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