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dc.contributor.authorRafferty, Josephen
dc.contributor.authorNugent, Chrisen
dc.contributor.authorLiu, Junen
dc.contributor.authorChen, Limingen
dc.date.accessioned2017-03-08T09:47:00Z
dc.date.available2017-03-08T09:47:00Z
dc.date.issued2017-01-05
dc.identifier.citationRafferty, J et al. (2017) From Activity Recognition to Intention Recognition for Assisted Living Within Smart Homes. IEEE Transactions on Human-Machine Systems, 47 (3), pp. 368-379en
dc.identifier.issn2168-2291
dc.identifier.urihttp://hdl.handle.net/2086/13456
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractThe global population is aging; projections show that by 2050, more than 20% of the population will be aged over 64. This will lead to an increase in aging related illness, a decrease in informal support, and ultimately issues with providing care for these individuals. Assistive smart homes provide a promising solution to some of these issues. Nevertheless, they currently have issues hindering their adoption. To help address some of these issues, this study introduces a novel approach to implementing assistive smart homes. The devised approach is based upon an intention recognition mechanism incorporated into an intelligent agent architecture. This approach is detailed and evaluated. Evaluation was performed across three scenarios. Scenario 1 involved a web interface, focusing on testing the intention recognition mechanism. Scenarios 2 and 3 involved retrofitting a home with sensors and providing assistance with activities over a period of 3 months. The average accuracy for these three scenarios was 100%, 64.4%, and 83.3%, respectively. Future will extend and further evaluate this approach by implementing advanced sensor-filtering rules and evaluating more complex activities.en
dc.publisherIEEE Transactions on Human-Machine Systemsen
dc.subjectIntelligent agentsen
dc.subjectActivity recognitionen
dc.subjectSmart homesen
dc.subjectHidden Markov modelsen
dc.subjectAgingen
dc.subjectIntelligent sensorsen
dc.titleFrom Activity Recognition to Intention Recognition for Assisted Living Within Smart Homesen
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1109/THMS.2016.2641388
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceCC-BY-NDen
dc.date.acceptance2017-01-05en
dc.researchinstituteCyber Technology Institute (CTI)en


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