دورية أكاديمية
Multimodal Sensor Data Integration for Indoor Positioning in Ambient-Assisted Living Environments
| العنوان: | Multimodal Sensor Data Integration for Indoor Positioning in Ambient-Assisted Living Environments |
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| المؤلفون: | Sansano-Sansano, Emilio, Belmonte-Fernández, Óscar, Montoliu Colás, Raul, Gascó Compte, Arturo, Caballer Miedes, Antonio |
| بيانات النشر: | Hindawi |
| سنة النشر: | 2020 |
| المجموعة: | Repositori Universitat Jaume I (Repositorio UJI) |
| الوصف: | A reliable Indoor Positioning System (IPS) is a crucial part of the Ambient-Assisted Living (AAL) concept. The use of Wi-Fi fingerprinting techniques to determine the location of the user, based on the Received Signal Strength Indication (RSSI) mapping, avoids the need to deploy a dedicated positioning infrastructure but comes with its own issues. Heterogeneity of devices and RSSI variability in space and time due to environment changing conditions pose a challenge to positioning systems based on this technique. The primary purpose of this research is to examine the viability of leveraging other sensors in aiding the positioning system to provide more accurate predictions. In particular, the experiments presented in this work show that Inertial Motion Units (IMU), which are present by default in smart devices such as smartphones or smartwatches, can increase the performance of Indoor Positioning Systems in AAL environments. Furthermore, this paper assesses a set of techniques to predict the future performance of the positioning system based on the training data, as well as complementary strategies such as data scaling and the use of consecutive Wi-Fi scanning to further improve the reliability of the IPS predictions. This research shows that a robust positioning estimation can be derived from such strategies. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 1574-017X 1875-905X |
| العلاقة: | Mobile Information Systems, 2020, vol. 2020.; RTI2018-095168-B-C53, UJI-B2017-45, PRX18/00123; https://www.hindawi.com/journals/misy/2020/5204158Test/; SANSANO-SANSANO, Emilio, et al. Multimodal Sensor Data Integration for Indoor Positioning in Ambient-Assisted Living Environments. Mobile Information Systems, 2020, vol. 2020.; http://hdl.handle.net/10234/190255Test; https://doi.org/10.1155/2020/5204158Test |
| DOI: | 10.1155/2020/5204158 |
| الإتاحة: | https://doi.org/10.1155/2020/5204158Test http://hdl.handle.net/10234/190255Test |
| حقوق: | Copyright © 2020 Emilio Sansano-Sansano et al. *is 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. ; Atribución 4.0 Internacional ; http://creativecommons.org/licenses/by-sa/4.0Test/ ; info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.B7AA47A |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 1574017X 1875905X |
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| DOI: | 10.1155/2020/5204158 |