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Ambient intelligent framework for modelling critical medical events based on context awareness

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 14 No. 3 (2024)

DOI
10.11591/ijece.v14i3.pp3106-3115
ISSN
2722-2578, 2088-8708
Published
2024-06-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

With the rapid pace of communication technology, the modern communication system still encounters challenges in meeting the dynamic requirements of users. Facilitating emergency services for patients without a caretaker side by is quite challenging. This work contributes a solution towards state-of-the-art research problems by introducing a novel architecture using collaboration, coordination and user activity detection using contextual information. A prototype is built and experiment is carried out to emphasize the importance of real-time activity-based context awareness in ambient intelligence (AmI) applications. The primary contributions of this work are introduction of novel architecture and usage of both static and dynamic activity-based contextual parameters. The secondary contribution of this model is to integrate ambient intelligence with context awareness to offer higher accuracy in determining the critical condition of a patient. Initially, analytical models are built using the context-based attributes that consider both clinical and non-clinical entities based on the minimal and essential vital information of patient. This paper further discusses the experimental model, which is highly cost-efficient both from an operational and usage viewpoint. Different assessment environments have been used for assessing the performance of the model.

Collaboration network of the authors

2 authors · 1 co-authorship link

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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Ambient intelligent framework for modelling critical medical events based on context awareness</dc:title><dc:creator>Subramaniyam, Manjunath</dc:creator><dc:creator>Parthasar, Srirangapatna Sampathkumararan</dc:creator><dc:description>&lt;jats:p&gt;With the rapid pace of communication technology, the modern communication system still encounters challenges in meeting the dynamic requirements of users. Facilitating emergency services for patients without a caretaker side by is quite challenging. This work contributes a solution towards state-of-the-art research problems by introducing a novel architecture using collaboration, coordination and user activity detection using contextual information. A prototype is built and experiment is carried out to emphasize the importance of real-time activity-based context awareness in ambient intelligence (AmI) applications. The primary contributions of this work are introduction of novel architecture and usage of both static and dynamic activity-based contextual parameters. The secondary contribution of this model is to integrate ambient intelligence with context awareness to offer higher accuracy in determining the critical condition of a patient. Initially, analytical models are built using the context-based attributes that consider both clinical and non-clinical entities based on the minimal and essential vital information of patient. This paper further discusses the experimental model, which is highly cost-efficient both from an operational and usage viewpoint. Different assessment environments have been used for assessing the performance of the model.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2024-06-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v14i3.pp3106-3115</dc:identifier><dc:identifier>10.11591/ijece.v14i3.pp3106-3115</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 14 No 3 (2024); 3106</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/35229/17409</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>