Rule-based real-time ADL recognition in a smart home environment

George Baryannis; Przemyslaw Woznowski; Grigoris Antoniou

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

Rule-based real-time ADL recognition in a smart home environment

George Baryannis, Przemyslaw Woznowski, Grigoris Antoniou

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

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 - 10th International Symposium, RuleML 2016, Proceedings
Publisher	Springer Verlag
Pages	325-340
Number of pages	16
Volume	9718
ISBN (Print)	9783319420189
DOIs	https://doi.org/10.1007/978-3-319-42019-6_21
Publication status	Published - 28 Jun 2016
Event	10th International Symposium on Rule Technologies - Stony Brook University, Stony Brook, United States Duration: 6 Jul 2016 → 9 Jul 2016 http://2016.ruleml.org/ (Link to Conference Website)

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9718
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Symposium on Rule Technologies
Abbreviated title	RuleML 2016
Country/Territory	United States
City	Stony Brook
Period	6/07/16 → 9/07/16
Internet address	http://2016.ruleml.org/ (Link to Conference Website)

Access to Document

10.1007/978-3-319-42019-6_21Licence: Other

http://eprints.hud.ac.uk/id/eprint/29003/Licence: Unspecified

Cite this

Baryannis, G., Woznowski, P., & Antoniou, G. (2016). Rule-based real-time ADL recognition in a smart home environment. In Rule Technologies: Research, Tools, and Applications - 10th International Symposium, RuleML 2016, Proceedings (Vol. 9718, pp. 325-340). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9718). Springer Verlag. https://doi.org/10.1007/978-3-319-42019-6_21

Baryannis, George ; Woznowski, Przemyslaw ; Antoniou, Grigoris. / Rule-based real-time ADL recognition in a smart home environment. Rule Technologies: Research, Tools, and Applications - 10th International Symposium, RuleML 2016, Proceedings. Vol. 9718 Springer Verlag, 2016. pp. 325-340 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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Baryannis, G, Woznowski, P & Antoniou, G 2016, Rule-based real-time ADL recognition in a smart home environment. in Rule Technologies: Research, Tools, and Applications - 10th International Symposium, RuleML 2016, Proceedings. vol. 9718, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9718, Springer Verlag, pp. 325-340, 10th International Symposium on Rule Technologies, Stony Brook, New York, United States, 6/07/16. https://doi.org/10.1007/978-3-319-42019-6_21

Rule-based real-time ADL recognition in a smart home environment. / Baryannis, George; Woznowski, Przemyslaw; Antoniou, Grigoris.

Rule Technologies: Research, Tools, and Applications - 10th International Symposium, RuleML 2016, Proceedings. Vol. 9718 Springer Verlag, 2016. p. 325-340 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9718).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Antoniou, Grigoris

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Y1 - 2016/6/28

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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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Baryannis G, Woznowski P, Antoniou G. Rule-based real-time ADL recognition in a smart home environment. In Rule Technologies: Research, Tools, and Applications - 10th International Symposium, RuleML 2016, Proceedings. Vol. 9718. Springer Verlag. 2016. p. 325-340. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-42019-6_21

Rule-based real-time ADL recognition in a smart home environment

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