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DOMUS: a domestic ontology managed ubiquitous system

Articolo
Data di Pubblicazione:
2021
Abstract:
In the last decades, researches in the fields of Ambient Assisted Living and Smart Home have adopted technological paradigms to provide inhabitants with tailored solutions able to help them in their daily life, enable energy savings and monitor safety. Within this context, this paper introduces DOMUS, a Domestic Ontology Managed Ubiquitous System aimed at enabling the Smart Home paradigm and supporting dwellers characterized by frailty in autonomous living, a condition affecting elderlies in both physical and cognitive ways. DOMUS leverages ontological modelling of many domains of knowledge to customize indoor comfort management and to assist the dwellers in some of their Activities of Daily Living. The presented system exploits the semantic modeling of inhabitant's health-related concepts to trigger the actuation of indoor comfort metrics inside the domestic environment. DOMUS's complexity is hidden to the dwellers, who can interact with the system via an adaptive ubiquitous interface--the Home Interactive Controller (HIC). In this work, DOMUS's architecture and its ontological framework are described in detail. Also, the functionalities provided via HIC and dedicated to the inhabitants are presented, focusing on customization of comfort and assistance in the process of meal preparation. Preliminary tests concerning the inferences produced by the ontologies, the evaluation of the usability of the system and its acceptance from target users are also presented: the first results highlight a good level of usability of DOMUS through the HIC, while its level of acceptance is encouraging and suggests some improvements.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
ontology engineering; smart environment; smart home architecture; ontology-based decision support system
Elenco autori:
Spoladore, Daniele; Mahroo, Atieh; Sacco, Marco
Autori di Ateneo:
SACCO MARCO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/441338
Pubblicato in:
JOURNAL OF AMBIENT INTELLIGENCE & HUMANIZED COMPUTING (PRINT)
Journal
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http://www.scopus.com/record/display.url?eid=2-s2.0-85103424874&origin=inward
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