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Abstract
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.
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Authors and Affiliations
Dipartimento di Matematica e Informatica, Università della Calabria, I87036, Rende, CS, Italy
Francesco Cauteruccio & Giorgio Terracina
Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica, Università della Calabria, I87036, Rende, CS, Italy
Giancarlo Fortino & Antonio Guerrieri
- Francesco Cauteruccio
Search author on:PubMed Google Scholar
- Giancarlo Fortino
Search author on:PubMed Google Scholar
- Antonio Guerrieri
Search author on:PubMed Google Scholar
- Giorgio Terracina
Search author on:PubMed Google Scholar
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Editors and Affiliations
Department of Informatics, Modelling, Electronics and Systems (DIMES), University of Calabria (UNICAL), Rende, Italy
Giancarlo Fortino
The University of Reading, Whiteknights, Reading, RG6 6AY, Berkshire, UK
Giuseppe Di Fatta
School of Logistics Engineering, Wuhan University of Technology, Wuhan, P.R. China
Wenfeng Li
Computer Science Department, Universidad de Chile, Chile
Sergio Ochoa
ICAR-CNR and University of Calabria, Italy
Alfredo Cuzzocrea
CSIRO ICT, Center, Room # 5124, 108 North Road, Acton, ACT 2601, Australia
Mukaddim Pathan
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Cauteruccio, F., Fortino, G., Guerrieri, A., Terracina, G. (2014). Discovery of Hidden Correlations between Heterogeneous Wireless Sensor Data Streams. In: Fortino, G., Di Fatta, G., Li, W., Ochoa, S., Cuzzocrea, A., Pathan, M. (eds) Internet and Distributed Computing Systems. IDCS 2014. Lecture Notes in Computer Science, vol 8729. Springer, Cham. https://doi.org/10.1007/978-3-319-11692-1_33
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