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Proceedings 2018, 2(19), 1225; https://doi.org/10.3390/proceedings2191225

Real-time Recognition of Interleaved Activities Based on Ensemble Classifier of Long Short-Term Memory with Fuzzy Temporal Windows

1
Department of Computer Science, University of Jaén, Campus Las Lagunillas, 23071 Jaén, Spain
2
School of Computing, Ulster University, Newtownabbey, Co. Antrim, Northern Ireland BT15 1ED, UK
3
Department of Computer Science, University of Cádiz, Calle Ancha 16, 11001 Cádiz, Spain
Presented at the 12th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2018), Punta Cana, Dominican Republic, 4–7 December 2018.
*
Author to whom correspondence should be addressed.
Published: 26 October 2018
PDF [570 KB, uploaded 26 October 2018]

Abstract

In this paper, we present a methodology for Real-Time Activity Recognition of Interleaved Activities based on Fuzzy Logic and Recurrent Neural Networks. Firstly, we propose a representation of binary-sensor activations based on multiple Fuzzy Temporal Windows. Secondly, an ensemble of activity-based classifiers for balanced training and selection of relevant sensors is proposed. Each classifier is configured as a Long Short-Term Memory with self-reliant detection of interleaved activities. The proposed approach was evaluated using well-known interleaved binary-sensor datasets comprised of activities of daily living.
Keywords: real-time activity recognition; interleaved activities; fuzzy temporal windows; long short-term memory real-time activity recognition; interleaved activities; fuzzy temporal windows; long short-term memory
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Quero, J.M.; Orr, C.; Zang, S.; Nugent, C.; Salguero, A.; Espinilla, M. Real-time Recognition of Interleaved Activities Based on Ensemble Classifier of Long Short-Term Memory with Fuzzy Temporal Windows. Proceedings 2018, 2, 1225.

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