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Reinventing the energy bill in smart cities with NoSQL technologies

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Detalhes bibliográficos
Resumo:With the increasing use of electrical devices, cities consume more energy to sustain their daily activities, facing more challenges associated with energy control and distribution. This chapter revisits a previously proposed architecture to extract, load, transform, mine and forecast Big Data within a Smart City context, in order to discuss the adequacy of NoSQL databases to deliver a Smart City service that reinvents the traditional energy bill, using web and mobile applications. Citizens will benefit from a new form of self-monitoring their electricity and gas consumption, by comparing themselves to others within their cluster or region and by forecasting future energy consumptions. Moreover, the service also delivers to energy providers and cities a smarter overview of the energy landscape. The technological architecture was previously validated using simulated data from the United States of America (USA), due to its open availability, and revealed very satisfactory results concerning the performance of clustering and time series forecasting models. This chapter extends the previously proposed technological architecture, by providing real-time concurrent web and mobile access to citizens, while presenting a broad review of several NoSQL benchmarks available in the scientific community, knowledge that is essential in the adoption of a specific database to support these web and mobile applications.
Autores principais:Costa, Carlos
Outros Autores:Santos, Maribel Yasmina
Assunto:Big Data Clustering Energy Consumption Forecasting NoSQL NoSQL Benchmark Smart Cities Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Ano:2016
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:With the increasing use of electrical devices, cities consume more energy to sustain their daily activities, facing more challenges associated with energy control and distribution. This chapter revisits a previously proposed architecture to extract, load, transform, mine and forecast Big Data within a Smart City context, in order to discuss the adequacy of NoSQL databases to deliver a Smart City service that reinvents the traditional energy bill, using web and mobile applications. Citizens will benefit from a new form of self-monitoring their electricity and gas consumption, by comparing themselves to others within their cluster or region and by forecasting future energy consumptions. Moreover, the service also delivers to energy providers and cities a smarter overview of the energy landscape. The technological architecture was previously validated using simulated data from the United States of America (USA), due to its open availability, and revealed very satisfactory results concerning the performance of clustering and time series forecasting models. This chapter extends the previously proposed technological architecture, by providing real-time concurrent web and mobile access to citizens, while presenting a broad review of several NoSQL benchmarks available in the scientific community, knowledge that is essential in the adoption of a specific database to support these web and mobile applications.