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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/63880
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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 |
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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 |
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reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
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SEDICI (UNLP) |
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Universidad Nacional de La Plata |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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alira@sedici.unlp.edu.ar |
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score |
13.13397 |