Cooperative agent-based SANET architecture for personalised healthcare monitoring

Chaczko, Z; Chiu, C; Kale, A

Cooperative agent-based SANET architecture for personalised healthcare monitoring

Chaczko, Z

Chiu, C

Kale, A

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Publication Type:: Conference Proceeding
Citation:: 4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings, 2010
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.contributor.author	Chiu, C https://orcid.org/0000-0003-2045-5961	en_US
dc.contributor.author	Kale, A	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings, 2010	en_US
dc.identifier.isbn	9781424479078	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16180
dc.description.abstract	The application of an software agent-based computational technique that implements Extended Kohonen Maps (EKMs) for the management of Sensor-Actuator networks (SANETs) in health-care facilities. The agent-based model incorporates the BDI (Belief-Desire-Intention) Agent paradigms by Georgeff et al. EKMs perform the quantitative analysis of an algorithmic artificial neural network process by using an indirect-mapping EKM to self-organize. Current results show a combinatorial approach to optimization with EKMs provides an improvement in event trajectory estimation compared to standalone cooperative EKM processes to allow responsive event detection for patient monitoring scenarios. This will allow healthcare professionals to focus less on administrative tasks, and more on improving patient needs, particularly with people who are in need for dedicated care and round-the-clock monitoring. ©2010 IEEE.	en_US
dc.relation.ispartof	4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings	en_US
dc.relation.isbasedon	10.1109/ICSPCS.2010.5709690	en_US
dc.title	Cooperative agent-based SANET architecture for personalised healthcare monitoring	en_US
dc.type	Conference Proceeding
utslib.for	080309 Software Engineering	en_US
utslib.for	080101 Adaptive Agents and Intelligent Robotics	en_US
dc.location.activity	Gold Coast, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building/School of Architecture
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

The application of an software agent-based computational technique that implements Extended Kohonen Maps (EKMs) for the management of Sensor-Actuator networks (SANETs) in health-care facilities. The agent-based model incorporates the BDI (Belief-Desire-Intention) Agent paradigms by Georgeff et al. EKMs perform the quantitative analysis of an algorithmic artificial neural network process by using an indirect-mapping EKM to self-organize. Current results show a combinatorial approach to optimization with EKMs provides an improvement in event trajectory estimation compared to standalone cooperative EKM processes to allow responsive event detection for patient monitoring scenarios. This will allow healthcare professionals to focus less on administrative tasks, and more on improving patient needs, particularly with people who are in need for dedicated care and round-the-clock monitoring. ©2010 IEEE.

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http://hdl.handle.net/10453/16180