research-article

A probabilistic ontological framework for the recognition of multilevel human activities

Authors:

Daniele Riboni,

Heiner StuckenschmidtAuthors Info & Claims

UbiComp '13: Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing

Pages 345 - 354

https://doi.org/10.1145/2493432.2493501

Published: 08 September 2013 Publication History

Abstract

A major challenge of ubiquitous computing resides in the acquisition and modelling of rich and heterogeneous context data, among which, ongoing human activities at different degrees of granularity. In a previous work, we advocated the use of probabilistic description logics (DLs) in a multilevel activity recognition framework. In this paper, we present an in-depth study of activity modeling and reasoning within that framework, as well as an experimental evaluation with a large real-world dataset. Our solution allows us to cope with the uncertain nature of ontological descriptions of activities, while exploiting the expressive power and inference tools of the OWL 2 language. Targeting a large dataset of real human activities, we developed a probabilistic ontology modeling nearly 150 activities and actions of daily living. Experiments with a prototype implementation of our framework confirm the viability of our solution.

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Cited By

Kianpisheh MMariakakis ATruong K(2024)exHARProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435008:1(1-30)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643500
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
Vign� ASarthou GClodic A(2023)Primitive Action Recognition Based on�Semantic FactsSocial Robotics10.1007/978-981-99-8715-3_29(350-362)Online publication date: 3-Dec-2023
https://doi.org/10.1007/978-981-99-8715-3_29
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Index Terms

A probabilistic ontological framework for the recognition of multilevel human activities
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
2. Theory of computation
  1. Logic

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cover image ACM Conferences

UbiComp '13: Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing

September 2013

846 pages

ISBN:9781450317702

DOI:10.1145/2493432

General Chairs:
Friedemann Mattern
ETH Zurich, CH
,
Silvia Santini
TU Darmstadt, DE
,
Program Chairs:
John F. Canny
UC Berkeley, US
,
Marc Langheinrich
Universit� della Svizzera italiana, CH
,
Jun Rekimoto
University of Tokyo, JP

Copyright � 2013 ACM.

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Published: 08 September 2013

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UbiComp '13: The 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 8 - 12, 2013

Zurich, Switzerland

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UbiComp '13 Paper Acceptance Rate 92 of 394 submissions, 23%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

Kianpisheh MMariakakis ATruong K(2024)exHARProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435008:1(1-30)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643500
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
Vign� ASarthou GClodic A(2023)Primitive Action Recognition Based on�Semantic FactsSocial Robotics10.1007/978-981-99-8715-3_29(350-362)Online publication date: 3-Dec-2023
https://doi.org/10.1007/978-981-99-8715-3_29
Buoncompagni LKareem SMastrogiovanni F(2022)Human Activity Recognition Models in Ontology NetworksIEEE Transactions on Cybernetics10.1109/TCYB.2021.307353952:6(5587-5606)Online publication date: Jun-2022
https://doi.org/10.1109/TCYB.2021.3073539
Nagy LRuppert TAbonyi J(2022)Human-centered knowledge graph-based design concept for collaborative manufacturing2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)10.1109/ETFA52439.2022.9921484(1-8)Online publication date: 6-Sep-2022
https://doi.org/10.1109/ETFA52439.2022.9921484
Stavropoulos TMeditskos GLazarou IMpaltadoros LPapagiannopoulos STsolaki MKompatsiaris I(2021)Detection of Health-Related Events and Behaviours from Wearable Sensor Lifestyle Data Using Symbolic Intelligence: A Proof-of-Concept Application in the Care of Multiple SclerosisSensors10.3390/s2118623021:18(6230)Online publication date: 17-Sep-2021
https://doi.org/10.3390/s21186230
Alia SAdachi KHossain TLe NKaneko HLago POkita TInoue S(2021)Summary of the Third Nurse Care Activity Recognition Challenge - Can We Do from the Field Data?Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers10.1145/3460418.3479391(428-433)Online publication date: 21-Sep-2021
https://dl.acm.org/doi/10.1145/3460418.3479391
Alia SHossain TInoue S(2021)PerMML: A Performance Metric for Multi-layer DatasetAdjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers10.1145/3460418.3479352(285-290)Online publication date: 21-Sep-2021
https://dl.acm.org/doi/10.1145/3460418.3479352
Alam MRoy NMisra A(2021)Tracking and Behavior Augmented Activity Recognition for Multiple InhabitantsIEEE Transactions on Mobile Computing10.1109/TMC.2019.293638220:1(247-262)Online publication date: 1-Jan-2021
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Civitarese GSztyler TRiboni DBettini CStuckenschmidt H(2021)POLARIS: Probabilistic and Ontological Activity Recognition in Smart-HomesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2019.293005033:1(209-223)Online publication date: 1-Jan-2021
https://doi.org/10.1109/TKDE.2019.2930050
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