A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application

Accident prevention; Assisted living; Computer circuits; Fuzzy logic; Multi agent systems; Adjustable autonomy; Ambient assisted living; Autonomous decision; Complex environments; Elderly remote care; Fall detection; Fuzzy logic control; Movement monitoring; Autonomous agents; aged; Article; automat...

Full description

Saved in:
Bibliographic Details
Main Authors: Mostafa S.A., Mustapha A., Mohammed M.A., Ahmad M.S., Mahmoud M.A.
Other Authors: 37036085800
Format: Article
Published: Elsevier Ireland Ltd 2023
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-23861
record_format dspace
spelling my.uniten.dspace-238612023-05-29T14:52:30Z A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application Mostafa S.A. Mustapha A. Mohammed M.A. Ahmad M.S. Mahmoud M.A. 37036085800 57200530694 57192089894 56036880900 55247787300 Accident prevention; Assisted living; Computer circuits; Fuzzy logic; Multi agent systems; Adjustable autonomy; Ambient assisted living; Autonomous decision; Complex environments; Elderly remote care; Fall detection; Fuzzy logic control; Movement monitoring; Autonomous agents; aged; Article; automation; decision making; falling; fuzzy logic; human; movement (physiology); patient autonomy; patient monitoring; priority journal; algorithm; automated pattern recognition; computer simulation; movement (physiology); physiologic monitoring; procedures; theoretical model; Aged; Algorithms; Computer Simulation; Fuzzy Logic; Humans; Models, Theoretical; Monitoring, Physiologic; Movement; Pattern Recognition, Automated Autonomous agents are being widely used in many systems, such as ambient assisted-living systems, to perform tasks on behalf of humans. However, these systems usually operate in complex environments that entail uncertain, highly dynamic, or irregular workload. In such environments, autonomous agents tend to make decisions that lead to undesirable outcomes. In this paper, we propose a fuzzy-logic-based adjustable autonomy (FLAA) model to manage the autonomy of multi-agent systems that are operating in complex environments. This model aims to facilitate the autonomy management of agents and help them make competent autonomous decisions. The FLAA model employs fuzzy logic to quantitatively measure and distribute autonomy among several agents based on their performance. We implement and test this model in the Automated Elderly Movements Monitoring (AEMM-Care) system, which uses agents to monitor the daily movement activities of elderly users and perform fall detection and prevention tasks in a complex environment. The test results show that the FLAA model improves the accuracy and performance of these agents in detecting and preventing falls. � 2018 Elsevier B.V. Final 2023-05-29T06:52:30Z 2023-05-29T06:52:30Z 2018 Article 10.1016/j.ijmedinf.2018.02.001 2-s2.0-85041918630 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041918630&doi=10.1016%2fj.ijmedinf.2018.02.001&partnerID=40&md5=f1f28d3faca6bfd1d93ef051d0261519 https://irepository.uniten.edu.my/handle/123456789/23861 112 173 184 Elsevier Ireland Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Accident prevention; Assisted living; Computer circuits; Fuzzy logic; Multi agent systems; Adjustable autonomy; Ambient assisted living; Autonomous decision; Complex environments; Elderly remote care; Fall detection; Fuzzy logic control; Movement monitoring; Autonomous agents; aged; Article; automation; decision making; falling; fuzzy logic; human; movement (physiology); patient autonomy; patient monitoring; priority journal; algorithm; automated pattern recognition; computer simulation; movement (physiology); physiologic monitoring; procedures; theoretical model; Aged; Algorithms; Computer Simulation; Fuzzy Logic; Humans; Models, Theoretical; Monitoring, Physiologic; Movement; Pattern Recognition, Automated
author2 37036085800
author_facet 37036085800
Mostafa S.A.
Mustapha A.
Mohammed M.A.
Ahmad M.S.
Mahmoud M.A.
format Article
author Mostafa S.A.
Mustapha A.
Mohammed M.A.
Ahmad M.S.
Mahmoud M.A.
spellingShingle Mostafa S.A.
Mustapha A.
Mohammed M.A.
Ahmad M.S.
Mahmoud M.A.
A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application
author_sort Mostafa S.A.
title A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application
title_short A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application
title_full A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application
title_fullStr A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application
title_full_unstemmed A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application
title_sort fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application
publisher Elsevier Ireland Ltd
publishDate 2023
_version_ 1806424582520832000
score 13.209306