Archivio Istituzionale della RicercaThis chapter discusses different platforms for buildings exploiting novel technologies based on sensor networks, smart meters and database management systems to collect and store energy-related data. It also discusses novel analytical tools and data mining algorithms proposed in the literature for buildings to (i) characterize energy consumption, (ii) identify the main factors that increase energy consumption, (iii) detect faults, and (iv) enhance user energy awareness. Finally, the perspectives offered by energy-related data analytics are outlined, showing how analysis techniques can be profitably exploited to enhance user energy awareness and reduce building energy consumption.
Enhancing energy efficiency in buildings through innovative data analytics technologies / Capozzoli, Alfonso; Cerquitelli, Tania; Piscitelli, MARCO SAVINO - In: Pervasive Computing Next Generation Platforms for Intelligent Data Collection / Dobre C. , Xhafa F.. - STAMPA. - Cambridge, Massachusetts : Academic Press, 2016. - ISBN 978-0-12-803663-1. - pp. 353-389 [10.1016/B978-0-12-803663-1.00011-5]
Enhancing energy efficiency in buildings through innovative data analytics technologies
CAPOZZOLI, ALFONSO;CERQUITELLI, TANIA;PISCITELLI, MARCO SAVINO
2016
Abstract
This chapter discusses different platforms for buildings exploiting novel technologies based on sensor networks, smart meters and database management systems to collect and store energy-related data. It also discusses novel analytical tools and data mining algorithms proposed in the literature for buildings to (i) characterize energy consumption, (ii) identify the main factors that increase energy consumption, (iii) detect faults, and (iv) enhance user energy awareness. Finally, the perspectives offered by energy-related data analytics are outlined, showing how analysis techniques can be profitably exploited to enhance user energy awareness and reduce building energy consumption.
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https://hdl.handle.net/11583/2653542
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