An enhanced conceptual model for using ambient assisted living to provide a home proactive monitoring system for elderly saudi arabians

Alsulami, Majid Hamdan, ATKINS, Anthony, CAMPION, Russell and Alaboudi, Abdulellah Abdullah (2018) An enhanced conceptual model for using ambient assisted living to provide a home proactive monitoring system for elderly saudi arabians. Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, 2017-O. pp. 1443-1449. ISSN 2161-5330

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Abstract or description

The proportion of elderly people in the world population has increased and it is expected to increase further in the future. Changes in the number of children born per woman and mortality rates are major factors influencing the age profile of the population. In the Kingdom of Saudi Arabia, the proportion of elderly people in its population is expected to rise dramatically. Ambient Assisted Living (AAL) monitoring technology is an innovative form of technology that improves quality of life for elderly people and supports them with daily activities. AAL has potential to enable elderly people to live independently in their preferred environment and keep them connected with their families, relatives and friends. This paper aims to further enhance a conceptual model that was designed by the authors in 2016 to interconnect approved family members/ friends using smart phones/ tablets. The enhanced conceptual model will assist the Saudi government and elderly people to adopt AAL technology that supports early intervention at home and to minimise long term consequences of health issues. © 2017 IEEE.

Item Type:	Article
Additional Information:	Presented at The Conference of 14th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2017 ; Conference Date: 30 October 2017 - 3 November 2017; Conference Code:135250
Faculty:	School of Computing and Digital Technologies > Computing
Depositing User:	Library STORE team
Date Deposited:	15 Jun 2018 10:43
Last Modified:	24 Feb 2023 13:51
URI:	https://eprints.staffs.ac.uk/id/eprint/4422

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