Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot

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Título: Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot
Autor/es: Gomez-Donoso, Francisco | Escalona, Félix | Rivas, Francisco Miguel | Cañas, Jose Maria | Cazorla, Miguel
Grupo/s de investigación o GITE: Robótica y Visión Tridimensional (RoViT)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial | Universidad de Alicante. Instituto Universitario de Investigación Informática
Palabras clave: Ambient assisted living | Mobile robot
Área/s de conocimiento: Ciencia de la Computación e Inteligencia Artificial
Fecha de publicación: 2-abr-2019
Editor: Hindawi Publishing Corporation
Cita bibliográfica: Computational Intelligence and Neuroscience. Volume 2019, Article ID 9412384, 15 pages. doi:10.1155/2019/9412384
Resumen: Ambient assisted living (AAL) environments are currently a key focus of interest as an option to assist and monitor disabled and elderly people. These systems can improve their quality of life and personal autonomy by detecting events such as entering potentially dangerous areas, potential fall events, or extended stays in the same place. Nonetheless, there are areas that remain outside the scope of AAL systems due to the placement of cameras. There also exist sources of danger in the scope of the camera that the AAL system cannot detect. These sources of danger are relatively small in size, occluded, or nonstatic. To solve this problem, we propose the inclusion of a robot which maps such uncovered areas looking for new potentially dangerous areas that go unnoticed by the AAL. The robot then sends this information to the AAL system in order to improve its performance. Experimentation in real-life scenarios successfully validates our approach.
Patrocinador/es: This work was supported by the Spanish Government TIN2016-76515R Grant, supported with FEDER funds. This work was also supported by a Spanish grant for PhD studies (ACIF/2017/243 and FPU16/00887).
URI: http://hdl.handle.net/10045/91069
ISSN: 1687-5265 (Print) | 1687-5273 (Online)
DOI: 10.1155/2019/9412384
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © 2019 Francisco Gomez-Donoso et al. 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.
Revisión científica: si
Versión del editor: https://doi.org/10.1155/2019/9412384
Aparece en las colecciones:INV - RoViT - Artículos de Revistas

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