Ве молиме користете го овој идентификатор да го цитирате или поврзете овој запис: http://hdl.handle.net/20.500.12188/20775
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dc.contributor.authorDimitrievski, Aceen_US
dc.contributor.authorZdravevski, Eftimen_US
dc.contributor.authorLameski, Petreen_US
dc.contributor.authorTrajkovikj, Vladmiren_US
dc.date.accessioned2022-07-14T11:20:34Z-
dc.date.available2022-07-14T11:20:34Z-
dc.date.issued2016-09-08-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/20775-
dc.description.abstractAs the research in Ambient Assisted Living (AAL) matures, we expect that data generated from AAL IoT devices will benefit from analysis by well established machine learning techniques. There is also potential that new research in ML and Artificial Intelligence (AI) can be used on data generated from the sensors used in AAL. In this paper we present a survey of the research in the related topics, identify its shortcomings and propose future work that will integrate these fields by collecting ambient sensor data and process the data by ML framework which can detect and classify activities.en_US
dc.publisherIEEEen_US
dc.subjectAmbient Assisted Living, Machine Learning, Pervasive Computing, Ambient Intelligence, Wearable sensors, Environmental sensorsen_US
dc.titleA survey of Ambient Assisted Living systems: Challenges and opportunitiesen_US
dc.typeProceeding articleen_US
dc.relation.conference2016 IEEE 12th international conference on intelligent computer communication and processing (ICCP)en_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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