Conference paper:
Proceedings of Models@run.time 2013, September 2013. pp. 52-62. Nelly Bencomo, Robert B. France, Sebastian Götz, Bernhard Rumpe, editors. CEUR-WS.org.
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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.
@InProceedings{ jacquet2013mrt,
author = {Christophe Jacquet and Ahmed Mohamed and Frédéric Boulanger and Cécile Hardebolle and Yacine Bellik},
publisher = {CEUR-WS.org},
title = {{Building heterogeneous models at runtime to detect faults in ambient-intelligent environments}},
series = {CEUR Workshop Proceedings},
booktitle = {{Proceedings of Models@run.time 2013}},
month = {September},
volume = {1079},
year = {2013},
pages = {52-62},
}