Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/20775
Title: | A survey of Ambient Assisted Living systems: Challenges and opportunities | Authors: | Dimitrievski, Ace Zdravevski, Eftim Lameski, Petre Trajkovikj, Vladmir |
Keywords: | Ambient Assisted Living, Machine Learning, Pervasive Computing, Ambient Intelligence, Wearable sensors, Environmental sensors | Issue Date: | 8-Sep-2016 | Publisher: | IEEE | Conference: | 2016 IEEE 12th international conference on intelligent computer communication and processing (ICCP) | Abstract: | As 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. | URI: | http://hdl.handle.net/20.500.12188/20775 |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
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