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http://hdl.handle.net/20.500.12188/33492
Title: | Internet of Things Ontologies for Well-Being, Aging and Health: A Scoping Literature Review | Authors: | Belani, Hrvoje Šolić, Petar Zdravevski, Eftim Trajkovik, Vladimir |
Issue Date: | 20-Jan-2025 | Publisher: | MDPI AG | Journal: | Electronics | Abstract: | <jats:p>Internet of Things aims to simplify and automate complicated tasks by using sensors and other inputs for collecting huge amounts of data, processing them in the cloud and on the edge networks, and allowing decision making toward further interactions via actuators and other outputs. As connected IoT devices rank in billions, semantic interoperability remains one of the permanent challenges, where ontologies can provide a great contribution. The main goal of this paper is to analyze the state of research on semantic interoperability in well-being, aging, and health IoT services by using ontologies. This was achieved by analyzing the following research questions: “Which IoT ontologies have been used to implement well-being, aging and health services?” and “What is the dominant approach to achieve semantic interoperability of IoT solutions for well-being, aging and health?’ We conducted a scoping literature review of research papers from 2013 to 2024 by applying the PRISMA-ScR meta-analysis methodology with a custom-built software tool for an exhaustive search through the following digital libraries: IEEE Xplore, PubMed, MDPI, Elsevier ScienceDirect, and Springer Nature Link. By thoroughly analyzing 30 studies from an initial pool of more than 80,000 studies, we conclude that IoT ontologies for well-being, aging, and health services increasingly adopt Semantic Web of Things standards to achieve semantic interoperability by integrating heterogeneous data through unified semantic models. Emerging approaches, like semantic communication, Large Language Models Edge Intelligence, and sustainability-driven IoT analytics, can further enhance service efficiency and promote a holistic “One Well-Being, Aging, and Health” framework.</jats:p> | URI: | http://hdl.handle.net/20.500.12188/33492 | DOI: | 10.3390/electronics14020394 |
Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
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