Towards an Ontology for User Activities on Smart Environments

Most applications in smart environments must obtain data about their users and represent them (their context). One of the problems to be addressed in this domain is the user context representation. One of the main categories of context information in smart environments is user activity. This paper presents a mapping of the recent literature corresponding to human activity modeling using ontologies. Based on the results of this analysis, this work presents an ontology for representing human activities in smart spaces called ActivEOn. This ontology contains a high-level modeling of activities and related concepts that can be extended for specific domains. Two case studies using Protégé software demonstrated the developed ontology's potential.

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Published
2024-10-14
DOI
https://doi.org/10.5753/sbbd.2024.241224
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Towards an Ontology for User Activities on Smart Environments

Leonardo Vianna do Nascimento, José Palazzo Moreira de Oliveira
Context-Aware Activity Recognition Systems
article

Towards an Ontology for User Activities on Smart Environments

Leonardo Vianna do Nascimento, José Palazzo Moreira de Oliveira
article en

Abstract

Most applications in smart environments must obtain data about their users and represent them (their context). One of the problems to be addressed in this domain is the user context representation. One of the main categories of context information in smart environments is user activity. This paper presents a mapping of the recent literature corresponding to human activity modeling using ontologies. Based on the results of this analysis, this work presents an ontology for representing human activities in smart spaces called ActivEOn. This ontology contains a high-level modeling of activities and related concepts that can be extended for specific domains. Two case studies using Protégé software demonstrated the developed ontology's potential.

Universidade Federal do Rio Grande do Sul (BR), Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (BR), University of Rio Grande and Rio Grande Community College (US)
Ministério da Ciência, Tecnologia e Inovação, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 81%
Context-Aware Activity Recognition Systems
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