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dc.contributor.authorChand, G.
dc.contributor.authorAli M.
dc.contributor.authorBarmada, Bashar
dc.contributor.authorLiesaputra, Veronica
dc.contributor.authorPrado, G.
dc.contributor.editorC. Pahl, J. Yin
dc.contributor.editor. M. Vukovic,. Q. Yu
dc.date.accessioned2019-10-30T19:16:55Z
dc.date.available2019-10-30T19:16:55Z
dc.date.issued2018-11
dc.identifier.isbn978-3-030-03595-2
dc.identifier.isbn978-3-030-03596-9
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/10652/4765
dc.description.abstractThis paper proposes to use machine learning techniques with ultrasonic sensors to predict the behavior and status of a person when they live solely inside their house. The proposed system is tested on a single room. A grid of ultrasonic sensors is placed in the ceiling of a room to monitor the position and the status of a person (standing, sitting, lying down). The sensors readings are wirelessly communicated through a microcontroller to a cloud. An intelligent system will read the sensors values from the cloud and analyses them using machine learning algorithms to predict the person behavior and status and decide whether it is a normal situation or abnormal. If an abnormal situation is concluded, then an alert with be risen on a dashboard, where a care giver can take an immediate action. The proposed system managed to give results with accuracy exceeding 90%. Results out of this project will help people with supported needed, for example elderly people, to live their life as independent as possible, without too much interference from the caregivers. This will also free the care givers and allows them to monitors more units at the same time.en_NZ
dc.language.isoenen_NZ
dc.publisherSpringer Verlagen_NZ
dc.subjectsmart homesen_NZ
dc.subjectpeople with supported needsen_NZ
dc.subjectbehaviour trackingen_NZ
dc.subjectultrasonic sensorsen_NZ
dc.subjectmachine learningen_NZ
dc.subjectolder peopleen_NZ
dc.subjectaged careen_NZ
dc.titleTracking a person’s behaviour in a smart houseen_NZ
dc.typeConference Contribution - Paper in Published Proceedingsen_NZ
dc.date.updated2018-12-17T13:30:07Z
dc.subject.marsden080101 Adaptive Agents and Intelligent Roboticsen_NZ
dc.subject.marsden111702 Aged Health Careen_NZ
dc.identifier.bibliographicCitationChand, G., Ali, M., Barmada, B., Liesaputra, V., & Prado, G. (2018). Tracking a Person’s Behaviour in a Smart House. In C. Pahl, J. Yin,. M. Vukovic,. Q. Yu (Ed.), The 16th International Conference on Service Oriented Computing (pp. 1-12).en_NZ
unitec.publication.spage1en_NZ
unitec.publication.lpage12en_NZ
unitec.publication.titleService-Oriented Computing 16th International Conference, ICSOC 2018 Hangzhou, China, November 12–15, 2018 Proceedingsen_NZ
unitec.conference.titleService-Oriented Computing 16th International Conference, ICSOC 2018en_NZ
unitec.conference.locationHangzhou, Zhejiang Province, Chinaen_NZ
unitec.conference.sdate2018-11-12
unitec.conference.edate2018-11-15
unitec.peerreviewedyesen_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
unitec.identifier.roms62895en_NZ
unitec.identifier.roms62801en_NZ
unitec.publication.placeBerlin, Germanyen_NZ
unitec.institution.studyareaComputing


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