IoT for smart home energy planning

Autores
Orsi, Emilio; Nesmachnow, Sergio
Año de publicación
2017
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This article presents a platform combining hardware and software for smart power consumption monitoring and planning in urban scenarios. The system integrates a hardware controller for energy efficiency, a communication protocol to improve data transmission, and a software module for planning and managing home devices. The proposed solution is implemented applying the Internet of Things paradigm, allowing the integration of computational intelligence techniques. A greedy algorithm is proposed for planning, according to user preferences and a maximum allowed power consumption. Results show that the power consumption of a water heater is reduced up to 38.9%, and two water heaters and one air conditioning can be optimized simultaneously without reducing the quality of service. These results suggest that the proposed approach is useful for home power consumption planning.
VIII Workshop Procesamiento de Señales y Sistemas de Tiempo Real (WPSTR).
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
smart grid
energy
demand management
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/63880

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oai_identifier_str oai:sedici.unlp.edu.ar:10915/63880
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling IoT for smart home energy planningOrsi, EmilioNesmachnow, SergioCiencias Informáticassmart gridenergydemand managementThis article presents a platform combining hardware and software for smart power consumption monitoring and planning in urban scenarios. The system integrates a hardware controller for energy efficiency, a communication protocol to improve data transmission, and a software module for planning and managing home devices. The proposed solution is implemented applying the Internet of Things paradigm, allowing the integration of computational intelligence techniques. A greedy algorithm is proposed for planning, according to user preferences and a maximum allowed power consumption. Results show that the power consumption of a water heater is reduced up to 38.9%, and two water heaters and one air conditioning can be optimized simultaneously without reducing the quality of service. These results suggest that the proposed approach is useful for home power consumption planning.VIII Workshop Procesamiento de Señales y Sistemas de Tiempo Real (WPSTR).Red de Universidades con Carreras en Informática (RedUNCI)2017-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1091-1100http://sedici.unlp.edu.ar/handle/10915/63880enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-1539-9info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:41:03Zoai:sedici.unlp.edu.ar:10915/63880Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:41:05.003SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv IoT for smart home energy planning
title IoT for smart home energy planning
spellingShingle IoT for smart home energy planning
Orsi, Emilio
Ciencias Informáticas
smart grid
energy
demand management
title_short IoT for smart home energy planning
title_full IoT for smart home energy planning
title_fullStr IoT for smart home energy planning
title_full_unstemmed IoT for smart home energy planning
title_sort IoT for smart home energy planning
dc.creator.none.fl_str_mv Orsi, Emilio
Nesmachnow, Sergio
author Orsi, Emilio
author_facet Orsi, Emilio
Nesmachnow, Sergio
author_role author
author2 Nesmachnow, Sergio
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
smart grid
energy
demand management
topic Ciencias Informáticas
smart grid
energy
demand management
dc.description.none.fl_txt_mv This article presents a platform combining hardware and software for smart power consumption monitoring and planning in urban scenarios. The system integrates a hardware controller for energy efficiency, a communication protocol to improve data transmission, and a software module for planning and managing home devices. The proposed solution is implemented applying the Internet of Things paradigm, allowing the integration of computational intelligence techniques. A greedy algorithm is proposed for planning, according to user preferences and a maximum allowed power consumption. Results show that the power consumption of a water heater is reduced up to 38.9%, and two water heaters and one air conditioning can be optimized simultaneously without reducing the quality of service. These results suggest that the proposed approach is useful for home power consumption planning.
VIII Workshop Procesamiento de Señales y Sistemas de Tiempo Real (WPSTR).
Red de Universidades con Carreras en Informática (RedUNCI)
description This article presents a platform combining hardware and software for smart power consumption monitoring and planning in urban scenarios. The system integrates a hardware controller for energy efficiency, a communication protocol to improve data transmission, and a software module for planning and managing home devices. The proposed solution is implemented applying the Internet of Things paradigm, allowing the integration of computational intelligence techniques. A greedy algorithm is proposed for planning, according to user preferences and a maximum allowed power consumption. Results show that the power consumption of a water heater is reduced up to 38.9%, and two water heaters and one air conditioning can be optimized simultaneously without reducing the quality of service. These results suggest that the proposed approach is useful for home power consumption planning.
publishDate 2017
dc.date.none.fl_str_mv 2017-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/63880
url http://sedici.unlp.edu.ar/handle/10915/63880
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-34-1539-9
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
1091-1100
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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