Information fusion for context awareness in intelligent environments
Main Author: | |
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Publication Date: | 2013 |
Other Authors: | , |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/1822/26651 |
Summary: | The development of intelligent environments requires handling of data perceived from users, received from environments and gathered from objects. Such data is often used to implement machine learning tasks in order to predict actions or to anticipate needs and wills, as well as to provide additional context in applications. Thus, it is often needed to perform operations upon collected data, such as pre-processing, information fusion of sensor data, and manage models from machine learning. These machine learning models may have impact on the performance of platforms and systems used to obtain intelligent environments. In this paper, it is addressed the issue of the development of middleware for intelligent systems, using techniques from information fusion and machine learning that provide context awareness and reduce the impact of information acquisition on both storage and energy efficiency. This discussion is presented in the context of PHESS, a project to ensure energetic sustainability, based on intelligent agents and multi-agent systems, where these techniques are applied. |
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Information fusion for context awareness in intelligent environmentsInformation fusionMachine learningIntelligent environmentsContext awarenessScience & TechnologyThe development of intelligent environments requires handling of data perceived from users, received from environments and gathered from objects. Such data is often used to implement machine learning tasks in order to predict actions or to anticipate needs and wills, as well as to provide additional context in applications. Thus, it is often needed to perform operations upon collected data, such as pre-processing, information fusion of sensor data, and manage models from machine learning. These machine learning models may have impact on the performance of platforms and systems used to obtain intelligent environments. In this paper, it is addressed the issue of the development of middleware for intelligent systems, using techniques from information fusion and machine learning that provide context awareness and reduce the impact of information acquisition on both storage and energy efficiency. This discussion is presented in the context of PHESS, a project to ensure energetic sustainability, based on intelligent agents and multi-agent systems, where these techniques are applied.SpringerUniversidade do MinhoSilva, FábioAnalide, CésarNovais, Paulo20132013-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/26651eng978-3-642-40845-80302-974310.1007/978-3-642-40846-5_26http://dx.doi.org/10.1007/978-3-642-40846-5_26info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:24:44Zoai:repositorium.sdum.uminho.pt:1822/26651Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:26:15.093356Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Information fusion for context awareness in intelligent environments |
title |
Information fusion for context awareness in intelligent environments |
spellingShingle |
Information fusion for context awareness in intelligent environments Silva, Fábio Information fusion Machine learning Intelligent environments Context awareness Science & Technology |
title_short |
Information fusion for context awareness in intelligent environments |
title_full |
Information fusion for context awareness in intelligent environments |
title_fullStr |
Information fusion for context awareness in intelligent environments |
title_full_unstemmed |
Information fusion for context awareness in intelligent environments |
title_sort |
Information fusion for context awareness in intelligent environments |
author |
Silva, Fábio |
author_facet |
Silva, Fábio Analide, César Novais, Paulo |
author_role |
author |
author2 |
Analide, César Novais, Paulo |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Silva, Fábio Analide, César Novais, Paulo |
dc.subject.por.fl_str_mv |
Information fusion Machine learning Intelligent environments Context awareness Science & Technology |
topic |
Information fusion Machine learning Intelligent environments Context awareness Science & Technology |
description |
The development of intelligent environments requires handling of data perceived from users, received from environments and gathered from objects. Such data is often used to implement machine learning tasks in order to predict actions or to anticipate needs and wills, as well as to provide additional context in applications. Thus, it is often needed to perform operations upon collected data, such as pre-processing, information fusion of sensor data, and manage models from machine learning. These machine learning models may have impact on the performance of platforms and systems used to obtain intelligent environments. In this paper, it is addressed the issue of the development of middleware for intelligent systems, using techniques from information fusion and machine learning that provide context awareness and reduce the impact of information acquisition on both storage and energy efficiency. This discussion is presented in the context of PHESS, a project to ensure energetic sustainability, based on intelligent agents and multi-agent systems, where these techniques are applied. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 2013-01-01T00:00:00Z |
dc.type.driver.fl_str_mv |
conference paper |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/26651 |
url |
http://hdl.handle.net/1822/26651 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
978-3-642-40845-8 0302-9743 10.1007/978-3-642-40846-5_26 http://dx.doi.org/10.1007/978-3-642-40846-5_26 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
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FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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1833595941823709184 |