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Opto-Electronic Smart Home: Heterogeneous Optical Sensors Approaches and Artificial Intelligence for Novel Paradigms in Remote Monitoring | IEEE Journals & Magazine | IEEE Xplore

Opto-Electronic Smart Home: Heterogeneous Optical Sensors Approaches and Artificial Intelligence for Novel Paradigms in Remote Monitoring


Abstract:

This article presents the development and implementation of an-optical fiber integrated smart environment with heterogeneous opto-electronic approaches. In this case, the...Show More

Abstract:

This article presents the development and implementation of an-optical fiber integrated smart environment with heterogeneous opto-electronic approaches. In this case, the so-called opto-electronic smart home is composed of three different optical fiber sensor system, which are also based on different optical fibers, resulting in more than 50 integrated sensors. The proposed smart environment is capable of detecting the location of the patient inside the home environment, recognize patient’s activities and provide the gait analysis through kinematics and spatio-temporal parameters of the gait. The heterogeneity of the system is verified by the use of the transmission-reflection analysis (TRA) using nanoparticle (NP)-doped optical fibers for the patient localization in Layer 1. Then, in Layer 2 a polymer optical fiber (POF) integrated pants is used by the patient, where the activity detection, especially walking, sitting and lying down is performed by the multiplexed intensity variation-based sensor integrated in the pants (with 30 sensors at each leg of the pants). Layer 3 comprises a fiber Bragg grating (FBG)-embedded smart carpet, where ten FBGs are inscribed in a single mode silica optical fiber. In addition, a graphical interface is developed for the sensors integration and cloud connectivity, where the signal processing is performed using the feedforward neural network (FFNN) approach for the location of mechanical perturbation along the optical fiber (for patient localization), activity classification and footsteps location along the FBG-embedded smart carpet. The implementation results show the feasibility of the proposed system, where the location of the patients, their activities and gait analysis.
Published in: IEEE Internet of Things Journal ( Volume: 11, Issue: 6, 15 March 2024)
Page(s): 9587 - 9598
Date of Publication: 10 October 2023

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