research-article

iKnow

Authors:

Georgios Meditskos,

Ioannis KompatsiarisAuthors Info & Claims

Pervasive and Mobile Computing, Volume 40, Issue C

Pages 17 - 41

https://doi.org/10.1016/j.pmcj.2017.05.003

Published: 01 September 2017 Publication History

Abstract

We present iKnow, an ontology-driven framework for semantic situation understanding in pervasive multi-sensor environments for human activity recognition. iKnow capitalises on the use of OWL ontological knowledge to capture domain relationships between low-level observations and high-level activities, while context aggregation and activity interpretation are supported through context-aware fusion. Rather than using ontologies as highly-structured, strict contextual models, our aim is to capture abstract dependencies among low- and high-level concepts, such as locations and objects involved in activities, towards addressing practical real-world challenges in the domain. The framework has been applied in the eminent field of healthcare, providing the models for the semantic enrichment and fusion of heterogeneous multisensory descriptors for monitoring the behaviour of people with Alzheimers disease.

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cover image Pervasive and Mobile Computing

Pervasive and Mobile Computing Volume 40, Issue C

September 2017

723 pages

ISSN:1574-1192

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Copyright © Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

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Published: 01 September 2017

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Boovaraghavan SPatidar PAgarwal Y(2023)TAOProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36108967:3(1-32)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610896
Boovaraghavan SChen CMaravi ACzapik MZhang YHarrison CAgarwal Y(2023)MitesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808657:1(1-32)Online publication date: 28-Mar-2023
https://dl.acm.org/doi/10.1145/3580865
Moulouel KChibani AAmirat Y(2023)Ontology-based hybrid commonsense reasoning framework for handling context abnormalities in uncertain and partially observable environmentsInformation Sciences: an International Journal10.1016/j.ins.2023.02.078631:C(468-486)Online publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.ins.2023.02.078
Moulouel KChibani AAbdelkawy HAmirat Y(2022)Hybrid approach for anticipating human activities in Ambient Intelligence environments2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)10.1109/CASE49997.2022.9926669(2006-2011)Online publication date: 20-Aug-2022
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Lakehal AAlti ARoose P(2022)Real-time ontology-based context-aware situation reasoning framework in pervasive computingMultimedia Tools and Applications10.1007/s11042-022-12252-081:11(14913-14957)Online publication date: 1-May-2022
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Civitarese GYe JZampatti MBettini C(2021)Collaborative activity recognition with heterogeneous activity sets and privacy preferencesJournal of Ambient Intelligence and Smart Environments10.3233/AIS-21001813:6(433-452)Online publication date: 1-Jan-2021
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Liu YMu YChen KLi YGuo J(2020)Daily Activity Feature Selection in Smart Homes Based on Pearson Correlation CoefficientNeural Processing Letters10.1007/s11063-019-10185-851:2(1771-1787)Online publication date: 7-Jan-2020
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