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...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer Nature
2018
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/4862/1/AJ%202018%20%28129%29.pdf |
| _version_ | 1825709921934508032 |
|---|---|
| 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 |
| collection | UTHM |
| 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 |
| first_indexed | 2024-03-05T21:49:44Z |
| format | Article |
| id | uthm.eprints-4862 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:49:44Z |
| publishDate | 2018 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | 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 |
| 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 |
| title | 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_short | 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 |
| topic | QA Mathematics QA75 Electronic computers. Computer science T Technology (General) QA273-280 Probabilities. Mathematical statistics |
| url | http://eprints.uthm.edu.my/4862/1/AJ%202018%20%28129%29.pdf |
| work_keys_str_mv | AT amostafasalama afuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication AT mustaphaaida afuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication AT mohammedmazinabed afuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication AT ahmadmohdsharifuddin afuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication AT amahmoudmoamin afuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication AT amostafasalama fuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication AT mustaphaaida fuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication AT mohammedmazinabed fuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication AT ahmadmohdsharifuddin fuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication AT amahmoudmoamin fuzzylogiccontrolinadjustableautonomyofamultiagentsystemforanautomatedelderlymovementmonitoringapplication |