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A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning

Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of sensors have encouraged the development of smart environments, such as smart homes. Smart homes can offer home assistance services to improve the quality of life, autonomy, and health of their residents, especi...

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Autores principales: Bouchabou, Damien, Nguyen, Sao Mai, Lohr, Christophe, LeDuc, Benoit, Kanellos, Ioannis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469092/
https://www.ncbi.nlm.nih.gov/pubmed/34577243
http://dx.doi.org/10.3390/s21186037
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author Bouchabou, Damien
Nguyen, Sao Mai
Lohr, Christophe
LeDuc, Benoit
Kanellos, Ioannis
author_facet Bouchabou, Damien
Nguyen, Sao Mai
Lohr, Christophe
LeDuc, Benoit
Kanellos, Ioannis
author_sort Bouchabou, Damien
collection PubMed
description Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of sensors have encouraged the development of smart environments, such as smart homes. Smart homes can offer home assistance services to improve the quality of life, autonomy, and health of their residents, especially for the elderly and dependent. To provide such services, a smart home must be able to understand the daily activities of its residents. Techniques for recognizing human activity in smart homes are advancing daily. However, new challenges are emerging every day. In this paper, we present recent algorithms, works, challenges, and taxonomy of the field of human activity recognition in a smart home through ambient sensors. Moreover, since activity recognition in smart homes is a young field, we raise specific problems, as well as missing and needed contributions. However, we also propose directions, research opportunities, and solutions to accelerate advances in this field.
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spelling pubmed-84690922021-09-27 A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning Bouchabou, Damien Nguyen, Sao Mai Lohr, Christophe LeDuc, Benoit Kanellos, Ioannis Sensors (Basel) Review Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of sensors have encouraged the development of smart environments, such as smart homes. Smart homes can offer home assistance services to improve the quality of life, autonomy, and health of their residents, especially for the elderly and dependent. To provide such services, a smart home must be able to understand the daily activities of its residents. Techniques for recognizing human activity in smart homes are advancing daily. However, new challenges are emerging every day. In this paper, we present recent algorithms, works, challenges, and taxonomy of the field of human activity recognition in a smart home through ambient sensors. Moreover, since activity recognition in smart homes is a young field, we raise specific problems, as well as missing and needed contributions. However, we also propose directions, research opportunities, and solutions to accelerate advances in this field. MDPI 2021-09-09 /pmc/articles/PMC8469092/ /pubmed/34577243 http://dx.doi.org/10.3390/s21186037 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Bouchabou, Damien
Nguyen, Sao Mai
Lohr, Christophe
LeDuc, Benoit
Kanellos, Ioannis
A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning
title A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning
title_full A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning
title_fullStr A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning
title_full_unstemmed A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning
title_short A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning
title_sort survey of human activity recognition in smart homes based on iot sensors algorithms: taxonomies, challenges, and opportunities with deep learning
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469092/
https://www.ncbi.nlm.nih.gov/pubmed/34577243
http://dx.doi.org/10.3390/s21186037
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