Abstract
This paper shows the application of a soft sensor network for the detection of meteorological events. A set of hard (real) sensor are placed in a territory, where they measure heterogeneous quantities. Starting from their measurements, a soft sensor network provides useful information coming from the data. In this contribution we show how prediction and validation of data can be done through machine learning approach by collecting data from the historical series. Furthermore, we show how the cluster based on correlation analysis among the data achieved by the sensors can be sensibly different from the ones simply drawn on geographical distance.
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Notes
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In this manuscript we use the term “cluster” to indicate the set of hardware sensors used to forecast the measures of another hardware sensor.
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Maniscalco, U., Pilato, G., Vella, F. (2016). Soft Sensor Network for Environmental Monitoring. In: Pietro, G., Gallo, L., Howlett, R., Jain, L. (eds) Intelligent Interactive Multimedia Systems and Services 2016. Smart Innovation, Systems and Technologies, vol 55. Springer, Cham. https://doi.org/10.1007/978-3-319-39345-2_63
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DOI: https://doi.org/10.1007/978-3-319-39345-2_63
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