article

Dynamic sensor data segmentation for real-time knowledge-driven activity recognition

Authors:

Roy SterrittAuthors Info & Claims

Pervasive and Mobile Computing, Volume 10

Pages 155 - 172

https://doi.org/10.1016/j.pmcj.2012.11.004

Published: 01 February 2014 Publication History

Abstract

Approaches and algorithms for activity recognition have recently made substantial progress due to advancements in pervasive and mobile computing, smart environments and ambient assisted living. Nevertheless, it is still difficult to achieve real-time continuous activity recognition as sensor data segmentation remains a challenge. This paper presents a novel approach to real-time sensor data segmentation for continuous activity recognition. Central to the approach is a dynamic segmentation model, based on the notion of varied time windows, which can shrink and expand the segmentation window size by using temporal information of sensor data and activities as well as the state of activity recognition. The paper first analyzes the characteristics of activities of daily living from which the segmentation model that is applicable to a wide range of activity recognition scenarios is motivated and developed. It then describes the working mechanism and relevant algorithms of the model in the context of knowledge-driven activity recognition based on ontologies. The presented approach has been implemented in a prototype system and evaluated in a number of experiments. Results have shown average recognition accuracy above 83% in all experiments for real time activity recognition, which proves the approach and the underlying model.

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Cited By

Smith RDragone M(2023)Generalisable Dialogue-based Approach for Active Learning of Activities of Daily LivingACM Transactions on Interactive Intelligent Systems10.1145/361601713:3(1-37)Online publication date: 11-Sep-2023
https://dl.acm.org/doi/10.1145/3616017
Benkhaled SHemam M(2022)A Semantic Gateway for Internet of Things Interoperability at the Application LayerApplied Computer Systems10.2478/acss-2022-002127:2(198-206)Online publication date: 1-Dec-2022
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Li YYu LLiao JSu GAmmarah HLiu LWang S(2022)A single smartwatch-based segmentation approach in human activity recognitionPervasive and Mobile Computing10.1016/j.pmcj.2022.10160083:COnline publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.pmcj.2022.101600
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Dynamic sensor data segmentation for real-time knowledge-driven activity recognition
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Copyright © Elsevier B.V. © 2012.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 February 2014

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Cited By

Smith RDragone M(2023)Generalisable Dialogue-based Approach for Active Learning of Activities of Daily LivingACM Transactions on Interactive Intelligent Systems10.1145/361601713:3(1-37)Online publication date: 11-Sep-2023
https://dl.acm.org/doi/10.1145/3616017
Benkhaled SHemam M(2022)A Semantic Gateway for Internet of Things Interoperability at the Application LayerApplied Computer Systems10.2478/acss-2022-002127:2(198-206)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.2478/acss-2022-0021
Li YYu LLiao JSu GAmmarah HLiu LWang S(2022)A single smartwatch-based segmentation approach in human activity recognitionPervasive and Mobile Computing10.1016/j.pmcj.2022.10160083:COnline publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.pmcj.2022.101600
Dębski RDreżewski R(2022)Real-time surrogate-assisted preprocessing of streaming sensor dataComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2022.109422219:COnline publication date: 24-Dec-2022
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Wang LChu MSheng CChen PGao G(2022)Decision support system for real-time segmentation and identification algorithm for wires in mobile terminals using fuzzy AHP methodSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-022-07197-326:20(10915-10926)Online publication date: 1-Oct-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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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
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