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Water demand estimation and outlier detection from smart meter data using classification and Big Data methods

Autor
García, D.; González, D.; Quevedo, J.; Puig, V.; Saludes, J.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
2nd New Developments in IT & Water Conference
Any de l'edició
2015
Data de presentació
2015-02-09
Llibre d'actes
2nd New Developments in IT & Water Conference, 8-10 February 2015, Rotterdam (Holland)
Pàgina inicial
1
Pàgina final
8
Repositori
http://hdl.handle.net/2117/26473 Obrir en finestra nova
Resum
Automatic Meter Reading (AMR) systems are being deployed in many cities to obtain insight into the status and the behavior of District Metering Area (DMA) with more granularity. Until now, the water consumption readings of the population were taken one per month or one each two-months. In contrast, AMR systems provide hourly readings for households and more frequent readings for big consumers. On the one hand, this paper aims at predicting water demand and detect suspicious behaviors – e.g. a ...
Citació
Garcia, D. [et al.]. Water demand estimation and outlier detection from smart meter data using classification and Big Data methods. A: New Developments in IT & Water. "2nd New Developments in IT & Water Conference, 8-10 February 2015, Rotterdam (Holland)". Rotterdam: 2015, p. 1-8.
Paraules clau
Smart Meters, Water Demand, Clustering, Big Data
Grup de recerca
CS2AC-UPC - Supervision, Safety and Automatic Control
SAC - Sistemes Avançats de Control
SIC - Sistemes Intel·ligents de Control

Participants

Arxius