Neuro-Immune-Endocrine (NIE) models for emergency services interoperatibility

Chaczko, Z; Moses, P

Neuro-Immune-Endocrine (NIE) models for emergency services interoperatibility

Chaczko, Z

Moses, P

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, 4739 LNCS pp. 105 - 112
Issue Date:: 2007-12-01

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Field	Value	Language
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.contributor.author	Moses, P	en_US
dc.date.issued	2007-12-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, 4739 LNCS pp. 105 - 112	en_US
dc.identifier.isbn	9783540758662	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/1875
dc.description.abstract	Highly dynamic, re-configurable hardware, embedded software and communication networks are becoming very significant in operation of various emergency services. The key challenge in designing such systems is to provide a framework for interoperability of emergency services in disaster situations. The goal of the paper is to provide an insight into modelling techniques for studying emergency services interoperability functions in system design to avoid hidden points of failures. Concepts of artificial Neuro-Immune-Endocrine (NIE) homeostatic models [21] [22] [24] for autonomous self-configuring and self-healing systems are discussed. The paper features examples of collaborative software agents' behaviour in hostile environments, cooperating protocols, smart embedded devices and pro-active infrastructures in various areas related to emergency services operations. © Springer-Verlag Berlin Heidelberg 2007.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Neuro-Immune-Endocrine (NIE) models for emergency services interoperatibility	en_US
dc.type	Conference Proceeding
utslib.citation.volume	4739 LNCS	en_US
utslib.for	0803 Computer Software	en_US
dc.location.activity	Las Palmas de Gran Canaria, Spain	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 Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
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
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	4739 LNCS	en_US

Abstract:

Highly dynamic, re-configurable hardware, embedded software and communication networks are becoming very significant in operation of various emergency services. The key challenge in designing such systems is to provide a framework for interoperability of emergency services in disaster situations. The goal of the paper is to provide an insight into modelling techniques for studying emergency services interoperability functions in system design to avoid hidden points of failures. Concepts of artificial Neuro-Immune-Endocrine (NIE) homeostatic models [21] [22] [24] for autonomous self-configuring and self-healing systems are discussed. The paper features examples of collaborative software agents' behaviour in hostile environments, cooperating protocols, smart embedded devices and pro-active infrastructures in various areas related to emergency services operations. © Springer-Verlag Berlin Heidelberg 2007.

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http://hdl.handle.net/10453/1875