Undernutrition Prevention for Disabled and Elderly People in Smart Home with Bayesian Networks and RFID Sensors
Identifieur interne : 000143 ( Hal/Corpus ); précédent : 000142; suivant : 000144Undernutrition Prevention for Disabled and Elderly People in Smart Home with Bayesian Networks and RFID Sensors
Auteurs : Nathalie CisloSource :
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Abstract
Undernutrition prevention or detection for disabled or elderly people must be performed rapidly to avoid irremediable consequences. In this paper a classification of uncertainties centered on a meal notion is first proposed. Two of these uncertainties are developed in a smart home and homecare context. Meal preparation probability is evaluated by a simulation based on Naïve Bayesian Networks. To determine if a person is at risk of malnutrition or undernutrition, and to supervise prepared meal quality and quantity in terms of nutrients, the use of RFID tags is discussed, bringing many open issues for which additional sensors are proposed. This research work was initiated in a collaborative project called CaptHom.
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In this paper a classification of uncertainties centered on a meal notion is first proposed. Two of these uncertainties are developed in a smart home and homecare context. Meal preparation probability is evaluated by a simulation based on Naïve Bayesian Networks. To determine if a person is at risk of malnutrition or undernutrition, and to supervise prepared meal quality and quantity in terms of nutrients, the use of RFID tags is discussed, bringing many open issues for which additional sensors are proposed. This research work was initiated in a collaborative project called CaptHom.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Undernutrition Prevention for Disabled and Elderly People in Smart Home with Bayesian Networks and RFID Sensors</title><author role="crp"><persName><forename type="first">Nathalie</forename><forename type="middle">D.</forename><surname>Cislo</surname></persName><email>nathalie.cislo@bourges.univ-orleans.fr</email><idno type="halauthor">617386</idno><affiliation ref="#struct-98357"></affiliation></author><editor role="depositor"><persName><forename>Nathalie</forename><surname>Cislo</surname></persName><email>nathalie.cislo@bourges.univ-orleans.fr</email></editor><funder>Ministère de l'Industrie français, collectivités locales françaises</funder></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2011-06-14 18:27:43</date><date type="whenWritten">2010-06-22</date><date type="whenModified">2011-06-15 09:45:42</date><date type="whenReleased">2011-06-15 09:45:42</date><date type="whenProduced">2010-06-21</date><date type="whenEndEmbargoed">2011-06-14</date><ref type="file" target="https://hal.archives-ouvertes.fr/hal-00600423/document"><date notBefore="2011-06-14"></date></ref><ref type="file" subtype="greenPublisher" n="1" target="https://hal.archives-ouvertes.fr/hal-00600423/file/cislo_icost2010_undernutrition_prevention_smart_homes_bayesian_networks_rfid.pdf"><date notBefore="2011-06-14"></date></ref><ref type="annex" subtype="other" n="0" target="https://hal.archives-ouvertes.fr/hal-00600423/file/Poster_ICOST2010_Cislo_v2.pdf"><date notBefore="2011-06-14"></date></ref></edition><respStmt><resp>contributor</resp><name key="162593"><persName><forename>Nathalie</forename><surname>Cislo</surname></persName><email>nathalie.cislo@bourges.univ-orleans.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-00600423</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-00600423</idno><idno type="halBibtex">cislo:hal-00600423</idno><idno type="halRefHtml">8th International Conference on Smart Homes and Health Telematics, ICOST 2010, Jun 2010, Seoul, South Korea. pp.246 - 249, 2010</idno><idno type="halRef">8th International Conference on Smart Homes and Health Telematics, ICOST 2010, Jun 2010, Seoul, South Korea. pp.246 - 249, 2010</idno></publicationStmt><seriesStmt><idno type="stamp" n="UNIV-ORLEANS">Université d'Orléans</idno><idno type="stamp" n="MSL">Modelisation Systemes Langages</idno></seriesStmt><notesStmt><note type="commentary">We especially thank all our partners involved in the CAPTHOM project of the S2E2 cluster (Sciences and Systems of Electrical Energy), and the French Industry Ministry and locale authorities for their financial help</note><note type="audience" n="2">International</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Undernutrition Prevention for Disabled and Elderly People in Smart Home with Bayesian Networks and RFID Sensors</title><author role="crp"><persName><forename type="first">Nathalie</forename><forename type="middle">D.</forename><surname>Cislo</surname></persName><email>nathalie.cislo@bourges.univ-orleans.fr</email><idno type="halAuthorId">617386</idno><affiliation ref="#struct-98357"></affiliation></author></analytic><monogr><title level="m">ICOST</title><meeting><title>8th International Conference on Smart Homes and Health Telematics, ICOST 2010</title><date type="start">2010-06-21</date><date type="end">2010-06-25</date><settlement>Seoul</settlement><country key="KR">South Korea</country></meeting><imprint><biblScope unit="pp">246 - 249</biblScope><date type="datePub">2010</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">Gerontechnologies</term><term xml:lang="en">Disabled People</term><term xml:lang="en">Elderly People</term><term xml:lang="en">RFID Sensors</term><term xml:lang="en">Bayesian Networks</term><term xml:lang="en">Undernutrition Prevention</term><term xml:lang="en">Smart Home</term></keywords><classCode scheme="classification">I.2.8 Problem Solving, Control Methods, and Search - Graph and tree search strategies</classCode><classCode scheme="halDomain" n="info.info-iu">Computer Science [cs]/Ubiquitous Computing</classCode><classCode scheme="halDomain" n="info.info-ai">Computer Science [cs]/Artificial Intelligence [cs.AI]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">Undernutrition prevention or detection for disabled or elderly people must be performed rapidly to avoid irremediable consequences. In this paper a classification of uncertainties centered on a meal notion is first proposed. Two of these uncertainties are developed in a smart home and homecare context. Meal preparation probability is evaluated by a simulation based on Naïve Bayesian Networks. To determine if a person is at risk of malnutrition or undernutrition, and to supervise prepared meal quality and quantity in terms of nutrients, the use of RFID tags is discussed, bringing many open issues for which additional sensors are proposed. This research work was initiated in a collaborative project called CaptHom.</abstract><particDesc><org type="consortium">CAPTHOM Project</org></particDesc></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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