Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot
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 even...
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2019-01-01
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Series: | Computational Intelligence and Neuroscience |
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doaj-10d6855c8d0947dd97649af4bb9a57162020-11-24T21:52:57ZengHindawi LimitedComputational Intelligence and Neuroscience1687-52651687-52732019-01-01201910.1155/2019/94123849412384Enhancing the Ambient Assisted Living Capabilities with a Mobile RobotFrancisco Gomez-Donoso0Félix Escalona1Francisco Miguel Rivas2Jose Maria Cañas3Miguel Cazorla4Institute for Computer Research, University of Alicante, P.O. Box 99, 03080 Alicante, SpainInstitute for Computer Research, University of Alicante, P.O. Box 99, 03080 Alicante, SpainRoboticsLab-URJC, Universidad Rey Juan Carlos, Madrid, SpainRoboticsLab-URJC, Universidad Rey Juan Carlos, Madrid, SpainInstitute for Computer Research, University of Alicante, P.O. Box 99, 03080 Alicante, SpainAmbient 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.http://dx.doi.org/10.1155/2019/9412384 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Francisco Gomez-Donoso Félix Escalona Francisco Miguel Rivas Jose Maria Cañas Miguel Cazorla |
spellingShingle |
Francisco Gomez-Donoso Félix Escalona Francisco Miguel Rivas Jose Maria Cañas Miguel Cazorla Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot Computational Intelligence and Neuroscience |
author_facet |
Francisco Gomez-Donoso Félix Escalona Francisco Miguel Rivas Jose Maria Cañas Miguel Cazorla |
author_sort |
Francisco Gomez-Donoso |
title |
Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot |
title_short |
Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot |
title_full |
Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot |
title_fullStr |
Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot |
title_full_unstemmed |
Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot |
title_sort |
enhancing the ambient assisted living capabilities with a mobile robot |
publisher |
Hindawi Limited |
series |
Computational Intelligence and Neuroscience |
issn |
1687-5265 1687-5273 |
publishDate |
2019-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2019/9412384 |
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AT franciscogomezdonoso enhancingtheambientassistedlivingcapabilitieswithamobilerobot AT felixescalona enhancingtheambientassistedlivingcapabilitieswithamobilerobot AT franciscomiguelrivas enhancingtheambientassistedlivingcapabilitieswithamobilerobot AT josemariacanas enhancingtheambientassistedlivingcapabilitieswithamobilerobot AT miguelcazorla enhancingtheambientassistedlivingcapabilitieswithamobilerobot |
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