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. Keywords Soft sensor Monitoring Multivariate regression Environmental risk Wireless sensor network Intelligent Interactive Multimedia Systems and Services 2016Intelligent Interactive Multimedia Systems and Services 2016 Look Inside Reference tools Export citation Add to Papers Other actions About this Book Reprints and Permissions Share Share this content on Facebook Share this content on Twitter Share this content on LinkedIn
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. Keywords Soft sensor Monitoring Multivariate regression Environmental risk Wireless sensor network Intelligent Interactive Multimedia Systems and Services 2016Intelligent Interactive Multimedia Systems and Services 2016 Look Inside Reference tools Export citation Add to Papers Other actions About this Book Reprints and Permissions Share Share this content on Facebook Share this content on Twitter Share this content on LinkedIn
Soft sensor network for environmental monitoring
Maniscalco U;Pilato G;Vella F
2016
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. Keywords Soft sensor Monitoring Multivariate regression Environmental risk Wireless sensor network Intelligent Interactive Multimedia Systems and Services 2016Intelligent Interactive Multimedia Systems and Services 2016 Look Inside Reference tools Export citation Add to Papers Other actions About this Book Reprints and Permissions Share Share this content on Facebook Share this content on Twitter Share this content on LinkedInI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
