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dc.contributor.authorPirzada, Pireh
dc.contributor.authorWhite, Neil
dc.contributor.authorWilde, Adriana Gabriela
dc.identifier.citationPirzada , P , White , N & Wilde , A G 2018 , ' Sensors in smart homes for independent living of elderly ' , Paper presented at International Multi-Topic ICT Conference 2018 , Jamshoro , Pakistan , 25/04/18 - 27/04/18 .en
dc.identifier.otherPURE: 252891442
dc.identifier.otherPURE UUID: 2bc5f197-3831-4013-bb6b-50917d40cc48
dc.description.abstractA rapidly ageing population requires support systems which would enable them to preserve dwellers’ independence without compromising on their safety or their quality of life. Smart homes for the elderly have the potential to offer unobtrusive health and wellness monitoring. The aim is to provide a safe, independent living environment which can identify and predict problems by monitoring the activities of daily living (ADLs) of the inhabitants. For this, a system able to handle continuous streams of data is required. Such a system can extract the information by using appropriate classification and learning algorithms and thus allow the remote monitoring of health and wellbeing at a high level. The implementation requires: the use of appropriate sensing technologies, identification of ADLs, data pre-processing techniques and machine learning algorithms. This is challenging due to individual differences: such a system must be able to personalize individual needs. Our contribution was the design and implementation of a platform to smartly monitor health condition of elderly using sensor data from a smart home, through an interactive user interface which is user-friendly and multi- platform. This proof-of-concept used off-line data, with the view to extend to real-time data collection in the future, which could then be used to inform support providers remotely.
dc.rights© 2018, the Owner(s)/the Author(s). This work has been made available online in accordance with the publisher’s policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at
dc.subjectSmart Homesen
dc.subjectActivity recognitionen
dc.subjectUnobtrusive monitoringen
dc.subjectHealth Careen
dc.subjectMachine Learningen
dc.subjectLearning Algorithmsen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.titleSensors in smart homes for independent living of elderlyen
dc.typeConference paperen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.description.statusPeer revieweden

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