A platform for analysing huge amounts of data from households and photovoltaic and electrical vehicles: from data to information

Analytics is an essential procedure to acquire knowledge and support applications for determining electricity consumption in smart homes. Electricity variables measured by the smart meter (SM) produce a significant amount of data on consumers, making the data sets very sizable and the analytics comp...

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Detalhes bibliográficos
Autores: Montoya, Oscar Danilo, Gil-González, Walter, Hernández, Jesus C.
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2023
País:España
Recursos:Universidad de Jaén
Repositório:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/6665
Acesso em linha:https://www.mdpi.com/2079-9292/11/23/3991
https://doi.org/10.3390/electronics11233991
https://hdl.handle.net/10953/6665
Access Level:Acceso aberto
Palavra-chave:internet of things
data acquisition
cloud computing
big data analytics
load profile
smart meter
621.35
Descrição
Resumo:Analytics is an essential procedure to acquire knowledge and support applications for determining electricity consumption in smart homes. Electricity variables measured by the smart meter (SM) produce a significant amount of data on consumers, making the data sets very sizable and the analytics complex. Data mining and emerging cloud computing technologies make collecting, processing, and analysing the so-called big data possible. The monitoring and visualization of information aid in personalizing applications that benefit both homeowners and researchers in analysing consumer profiles. This paper presents a smart meter for household (SMH) to obtain load profiles and a new platform that allows the innovative analysis of captured Internet of Things data from smart homes, photovoltaics, and electrical vehicles. We propose the use of cloud systems to enable data-based services and address the challenges of complexities and resource demands for online and offline data processing, storage, and classification analysis. The requirements and system design components are discussed.