Abstract
In this paper, a data validation and reconstruction methodology that can be applied to the sensors used for real-time monitoring in water networks is presented. On the one hand, a validation approach based on quality levels is described to detect potential invalid and missing data. On the other hand, the reconstruction strategy is based on a set of temporal and spatial models used to estimate missing/invalid data with the model estimation providing the best fit. A software tool implementing the proposed data validation and reconstruction methodology is also presented. Finally, results obtained applying the proposed methodology on raw data of flow meters gathered from a real water network are also included to illustrate the performance of the proposed approach.
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Notes
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Both software tools are proprietary software.
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SAC format is a binary Mat-file containing a defined data structure.
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Django is a free open source web framework. Its primary goal is to facilitate the creation of complex, database-driven websites.
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Acknowledgements
This work is partially supported by CICYT SHERECS DPI-2011-26243 of the Spanish Ministry of Education, by EFFINET grant FP7-ICT-2012-318556 of the European Commission and by AGAUR Doctorat Industrial 2013-DI-041. The authors also wish to thank the support received by the company ATLL in the development of this work.
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García, D., Quevedo, J., Puig, V., Cugueró, M.À. (2016). Sensor Data Validation and Reconstruction in Water Networks: A Methodology and Software Implementation. In: Panayiotou, C., Ellinas, G., Kyriakides, E., Polycarpou, M. (eds) Critical Information Infrastructures Security. CRITIS 2014. Lecture Notes in Computer Science(), vol 8985. Springer, Cham. https://doi.org/10.1007/978-3-319-31664-2_10
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DOI: https://doi.org/10.1007/978-3-319-31664-2_10
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