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

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...

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Main Authors:	A. Mostafa, Salama, Mustapha, Aida, Mohammed, Mazin Abed, Ahmad, Mohd Sharifuddin, A. Mahmoud, Moamin
Format:	Article
Language:	English
Published:	Springer Nature 2018
Subjects:	QA Mathematics QA75 Electronic computers. Computer science T Technology (General) QA273-280 Probabilities. Mathematical statistics
Online Access:	http://eprints.uthm.edu.my/4862/1/AJ%202018%20%28129%29.pdf http://eprints.uthm.edu.my/4862/ https://doi.org/10.1016/j.ijmedinf.2018.02.001
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spelling	my.uthm.eprints.48622021-12-23T03:59:55Z http://eprints.uthm.edu.my/4862/ A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application A. Mostafa, Salama Mustapha, Aida Mohammed, Mazin Abed Ahmad, Mohd Sharifuddin A. Mahmoud, Moamin QA Mathematics QA75 Electronic computers. Computer science T Technology (General) QA273-280 Probabilities. Mathematical statistics 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 Springer Nature 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/4862/1/AJ%202018%20%28129%29.pdf A. Mostafa, Salama and Mustapha, Aida and Mohammed, Mazin Abed and Ahmad, Mohd Sharifuddin and A. Mahmoud, Moamin (2018) A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application. International Journal of Medical Informatics, 112. pp. 173-184. ISSN 1386-5056 https://doi.org/10.1016/j.ijmedinf.2018.02.001
institution	Universiti Tun Hussein Onn Malaysia
building	UTHM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tun Hussein Onn Malaysia
content_source	UTHM Institutional Repository
url_provider	http://eprints.uthm.edu.my/
language	English
topic	QA Mathematics QA75 Electronic computers. Computer science T Technology (General) QA273-280 Probabilities. Mathematical statistics
spellingShingle	QA Mathematics QA75 Electronic computers. Computer science T Technology (General) QA273-280 Probabilities. Mathematical statistics A. Mostafa, Salama Mustapha, Aida Mohammed, Mazin Abed Ahmad, Mohd Sharifuddin A. Mahmoud, Moamin A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application
description	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
format	Article
author	A. Mostafa, Salama Mustapha, Aida Mohammed, Mazin Abed Ahmad, Mohd Sharifuddin A. Mahmoud, Moamin
author_facet	A. Mostafa, Salama Mustapha, Aida Mohammed, Mazin Abed Ahmad, Mohd Sharifuddin A. Mahmoud, Moamin
author_sort	A. Mostafa, Salama
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	Springer Nature
publishDate	2018
url	http://eprints.uthm.edu.my/4862/1/AJ%202018%20%28129%29.pdf http://eprints.uthm.edu.my/4862/ https://doi.org/10.1016/j.ijmedinf.2018.02.001
_version_	1738581307359756288
score	13.211869

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

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