RT Journal Article
T1 Efficient Activity Recognition in Smart Homes Using Delayed Fuzzy Temporal Windows on Binary Sensors.
A1 Rebeen, Hamad
A1 Salguero-Hidalgo, Alberto Gabriel
A1 Bouguelia, Mohamed-Rafik
A1 Espinilla-Estévez, Macarena
A1 Medina-Quero, Javier
A2 Fotiadiis, Dimitrions
K1 Domótica
K1 Reconocimiento de formas
AB Human activity recognition has become an active research field over the past few years due to its wide application in various fields such as health-care, smart home monitoring, and surveillance. Existing approaches for activity recognition in smart homes have achieved promising results. Most of these approaches evaluate real-time recognition of activities using only sensor activations that precede the evaluation time (where the decision is made). However, in several critical situations, such as diagnosing people with dementia, “preceding sensor activations” are not always sufficient to accurately recognize the inhabitant's daily activities in each evaluated time. To improve performance, we propose a method that delays the recognition process in order to include some sensor activations that occur after the point in time where the decision needs to be made. For this, the proposed method uses multiple incremental fuzzy temporal windows to extract features from both preceding and some oncoming sensor activations. The proposed method is evaluated with two temporal deep learning models (convolutional neural network and long short-term memory), on a binary sensor dataset of real daily living activities. The experimental evaluation shows that the proposed method achieves significantly better results than the real-time approach, and that the representation with fuzzy temporal windows enhances performance within deep learning models.
PB IEEE
SN 2168-2194
YR 2019
FD 2019
LK https://hdl.handle.net/10630/35358
UL https://hdl.handle.net/10630/35358
LA eng
NO Hamad, R. A., Hidalgo, A. S., Bouguelia, M. R., Estevez, M. E., & Quero, J. M. (2019). Efficient activity recognition in smart homes using delayed fuzzy temporal windows on binary sensors. IEEE journal of biomedical and health informatics, 24(2), 387-395.
NO Política de acceso abierto tomada de: https://openpolicyfinder.jisc.ac.uk/id/publication/36844
NO Marie Sklodowska-Curie EU Framework for Research Innovation Horizon 2020 (Grant Number: 734355)
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026