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

Salama A. Mostafa, Aida Mustapha, Mazin Abed Mohammed, Mohd Sharifuddin Ahmad, Moamin A. Mahmoud

Research output: Contribution to journalArticle

23 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)173-184
Number of pages12
JournalInternational Journal of Medical Informatics
Publication statusPublished - Apr 2018


All Science Journal Classification (ASJC) codes

  • Health Informatics

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