This paper proposes a novel approach for monitoring heterogeneous wireless sensor networks and to identify hidden correlations between sensors. The technique is tested in an experimental environment based on the Building Management Framework. Results show that the proposed approach is actually capable of identifying hidden correlations, is robust to environment variations and is sensitive to sensors faults.
CITATION STYLE
Cauteruccio, F., Fortino, G., Guerrieri, A., & Terracina, G. (2014). Discovery of hidden correlations between heterogeneous wireless sensor data streams. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8729, 383–395. https://doi.org/10.1007/978-3-319-11692-1_33
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