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

Files in This Item:
File Description SizeFormat 
Survey-ambient-with-cover-page-v2.pdf362.11 kBAdobe PDFView/Open
Show full item record

Page view(s)

25
checked on May 13, 2024

Download(s)

28
checked on May 13, 2024

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.