Rule-Based Real-Time ADL Recognition in a Smart Home Environment

G Baryannis; Przemyslaw R Woznowski; Gregoris Antoniou

doi:10.1007/978-3-319-42019-6_21

Rule-Based Real-Time ADL Recognition in a Smart Home Environment

G Baryannis, Przemyslaw R Woznowski, Gregoris Antoniou

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

16 Citations (Scopus)

434 Downloads (Pure)

Abstract

This paper presents a rule-based approach for both offline and real-time recognition of Activities of Daily Living (ADL), leveraging events produced by a non-intrusive multi-modal sensor infrastructure deployed in a residential environment. Novel aspects of the approach include: the ability to recognise arbitrary scenarios of complex activities using bottom-up multi-level reasoning, starting from sensor events at the lowest level; an effective heuristics-based method for distinguishing between actual and ghost images in video data; and a highly accurate indoor localisation approach that fuses different sources of location information. The proposed approach is implemented as a rule-based system using Jess and is evaluated using data collected in a smart home environment. Experimental results show high levels of accuracy and performance, proving the effectiveness of the approach in real world setups.

Original language	English
Title of host publication	Rule Technologies. Research, Tools, and Applications
Subtitle of host publication	10th International Symposium, RuleML 2016, Stony Brook, NY, USA, July 6-9, 2016. Proceedings
Editors	Jose Julio Alferes, Leopoldo Bertossi, Guido Governatori, Paul Fodor, Dumitru Roman
Publisher	Springer
Pages	325-340
Number of pages	16
ISBN (Electronic)	9783319420196
ISBN (Print)	9783319420189
DOIs	https://doi.org/10.1007/978-3-319-42019-6_21
Publication status	Published - 2 Aug 2016

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer International Publishing
Volume	9718
ISSN (Print)	0302-9743

Research Groups and Themes

Digital Health
SPHERE

Keywords

Event driven architectures
Activity recognition
ADL
Indoor localisation
Smart home
Multi-modal sensing

Access to Document

10.1007/978-3-319-42019-6_21

Full-text PDF (accepted author manuscript)
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Springer at http://link.springer.com/chapter/10.1007%2F978-3-319-42019-6_21. Please refer to any applicable terms of use of the publisher.
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SPHERE (EPSRC IRC)
Craddock, I. J. (Principal Investigator), Coyle, D. T. (Principal Investigator), Flach, P. A. (Principal Investigator), Kaleshi, D. (Principal Investigator), Mirmehdi, M. (Principal Investigator), Piechocki, R. J. (Principal Investigator), Stark, B. H. (Principal Investigator), Ascione, R. (Co-Principal Investigator), Ashburn, A. M. (Collaborator), Burnett, M. E. (Collaborator), Damen, D. (Co-Principal Investigator), Gooberman-Hill, R. (Principal Investigator), Harwin, W. S. (Collaborator), Hilton, G. (Co-Principal Investigator), Holderbaum, W. (Collaborator), Holley, A. P. (Manager), Manchester, V. A. (Administrator), Meller, B. J. (Other ), Stack, E. (Collaborator) & Gilchrist, I. D. (Principal Investigator)
1/10/13 → 30/09/18
Project: Research, Parent

Cite this

Baryannis, G., Woznowski, P. R., & Antoniou , G. (2016). Rule-Based Real-Time ADL Recognition in a Smart Home Environment. In J. J. Alferes, L. Bertossi, G. Governatori, P. Fodor, & D. Roman (Eds.), Rule Technologies. Research, Tools, and Applications: 10th International Symposium, RuleML 2016, Stony Brook, NY, USA, July 6-9, 2016. Proceedings (pp. 325-340). (Lecture Notes in Computer Science; Vol. 9718). Springer. https://doi.org/10.1007/978-3-319-42019-6_21

Baryannis, G ; Woznowski, Przemyslaw R ; Antoniou , Gregoris. / Rule-Based Real-Time ADL Recognition in a Smart Home Environment. Rule Technologies. Research, Tools, and Applications: 10th International Symposium, RuleML 2016, Stony Brook, NY, USA, July 6-9, 2016. Proceedings. editor / Jose Julio Alferes ; Leopoldo Bertossi ; Guido Governatori ; Paul Fodor ; Dumitru Roman. Springer, 2016. pp. 325-340 (Lecture Notes in Computer Science).

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abstract = "This paper presents a rule-based approach for both offline and real-time recognition of Activities of Daily Living (ADL), leveraging events produced by a non-intrusive multi-modal sensor infrastructure deployed in a residential environment. Novel aspects of the approach include: the ability to recognise arbitrary scenarios of complex activities using bottom-up multi-level reasoning, starting from sensor events at the lowest level; an effective heuristics-based method for distinguishing between actual and ghost images in video data; and a highly accurate indoor localisation approach that fuses different sources of location information. The proposed approach is implemented as a rule-based system using Jess and is evaluated using data collected in a smart home environment. Experimental results show high levels of accuracy and performance, proving the effectiveness of the approach in real world setups.",

keywords = "Event driven architectures, Activity recognition, ADL, Indoor localisation, Smart home, Multi-modal sensing",

author = "G Baryannis and Woznowski, \{Przemyslaw R\} and Gregoris Antoniou",

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Baryannis, G, Woznowski, PR & Antoniou , G 2016, Rule-Based Real-Time ADL Recognition in a Smart Home Environment. in JJ Alferes, L Bertossi, G Governatori, P Fodor & D Roman (eds), Rule Technologies. Research, Tools, and Applications: 10th International Symposium, RuleML 2016, Stony Brook, NY, USA, July 6-9, 2016. Proceedings. Lecture Notes in Computer Science, vol. 9718, Springer, pp. 325-340. https://doi.org/10.1007/978-3-319-42019-6_21

Rule-Based Real-Time ADL Recognition in a Smart Home Environment. / Baryannis, G; Woznowski, Przemyslaw R; Antoniou , Gregoris.
Rule Technologies. Research, Tools, and Applications: 10th International Symposium, RuleML 2016, Stony Brook, NY, USA, July 6-9, 2016. Proceedings. ed. / Jose Julio Alferes; Leopoldo Bertossi; Guido Governatori; Paul Fodor; Dumitru Roman. Springer, 2016. p. 325-340 (Lecture Notes in Computer Science; Vol. 9718).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Rule-Based Real-Time ADL Recognition in a Smart Home Environment

AU - Baryannis, G

AU - Woznowski, Przemyslaw R

AU - Antoniou , Gregoris

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N2 - This paper presents a rule-based approach for both offline and real-time recognition of Activities of Daily Living (ADL), leveraging events produced by a non-intrusive multi-modal sensor infrastructure deployed in a residential environment. Novel aspects of the approach include: the ability to recognise arbitrary scenarios of complex activities using bottom-up multi-level reasoning, starting from sensor events at the lowest level; an effective heuristics-based method for distinguishing between actual and ghost images in video data; and a highly accurate indoor localisation approach that fuses different sources of location information. The proposed approach is implemented as a rule-based system using Jess and is evaluated using data collected in a smart home environment. Experimental results show high levels of accuracy and performance, proving the effectiveness of the approach in real world setups.

AB - This paper presents a rule-based approach for both offline and real-time recognition of Activities of Daily Living (ADL), leveraging events produced by a non-intrusive multi-modal sensor infrastructure deployed in a residential environment. Novel aspects of the approach include: the ability to recognise arbitrary scenarios of complex activities using bottom-up multi-level reasoning, starting from sensor events at the lowest level; an effective heuristics-based method for distinguishing between actual and ghost images in video data; and a highly accurate indoor localisation approach that fuses different sources of location information. The proposed approach is implemented as a rule-based system using Jess and is evaluated using data collected in a smart home environment. Experimental results show high levels of accuracy and performance, proving the effectiveness of the approach in real world setups.

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BT - Rule Technologies. Research, Tools, and Applications

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A2 - Bertossi, Leopoldo

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Baryannis G, Woznowski PR, Antoniou G. Rule-Based Real-Time ADL Recognition in a Smart Home Environment. In Alferes JJ, Bertossi L, Governatori G, Fodor P, Roman D, editors, Rule Technologies. Research, Tools, and Applications: 10th International Symposium, RuleML 2016, Stony Brook, NY, USA, July 6-9, 2016. Proceedings. Springer. 2016. p. 325-340. (Lecture Notes in Computer Science). Epub 2016 Jun 28. doi: 10.1007/978-3-319-42019-6_21

Rule-Based Real-Time ADL Recognition in a Smart Home Environment

Abstract

Publication series

Research Groups and Themes

Keywords

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Projects

SPHERE (EPSRC IRC)

Cite this