Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies
Activity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching ev...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/15/4227 |
| _version_ | 1797560900287201280 |
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| author | Andres Sanchez-Comas Kåre Synnes Josef Hallberg |
| author_facet | Andres Sanchez-Comas Kåre Synnes Josef Hallberg |
| author_sort | Andres Sanchez-Comas |
| collection | DOAJ |
| description | Activity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching even the people most in need. This study was strongly motivated because levels of development, deployment, and technology of AR solutions transferred to society and industry are based on software development, but also depend on the hardware devices used. The current paper identifies contributions to hardware uses for activity recognition through a scientific literature review in the Web of Science (WoS) database. This work found four dominant groups of technologies used for AR in SH and AAL—smartphones, wearables, video, and electronic components—and two emerging technologies: Wi-Fi and assistive robots. Many of these technologies overlap across many research works. Through bibliometric networks analysis, the present review identified some gaps and new potential combinations of technologies for advances in this emerging worldwide field and their uses. The review also relates the use of these six technologies in health conditions, health care, emotion recognition, occupancy, mobility, posture recognition, localization, fall detection, and generic activity recognition applications. The above can serve as a road map that allows readers to execute approachable projects and deploy applications in different socioeconomic contexts, and the possibility to establish networks with the community involved in this topic. This analysis shows that the research field in activity recognition accepts that specific goals cannot be achieved using one single hardware technology, but can be using joint solutions, this paper shows how such technology works in this regard. |
| first_indexed | 2024-03-10T18:07:17Z |
| format | Article |
| id | doaj.art-2215382509c44eccb4f9a501b3aa3998 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T18:07:17Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2215382509c44eccb4f9a501b3aa39982023-11-20T08:24:21ZengMDPI AGSensors1424-82202020-07-012015422710.3390/s20154227Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related TechnologiesAndres Sanchez-Comas0Kåre Synnes1Josef Hallberg2Department of Productivity and Innovation, Universidad de la Costa, Barranquilla 080 002, ColombiaDepartment of Computer Science, Electrical and Space Engineering, Luleå Tekniska Universitet, 971 87 Luleå, SwedenDepartment of Computer Science, Electrical and Space Engineering, Luleå Tekniska Universitet, 971 87 Luleå, SwedenActivity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching even the people most in need. This study was strongly motivated because levels of development, deployment, and technology of AR solutions transferred to society and industry are based on software development, but also depend on the hardware devices used. The current paper identifies contributions to hardware uses for activity recognition through a scientific literature review in the Web of Science (WoS) database. This work found four dominant groups of technologies used for AR in SH and AAL—smartphones, wearables, video, and electronic components—and two emerging technologies: Wi-Fi and assistive robots. Many of these technologies overlap across many research works. Through bibliometric networks analysis, the present review identified some gaps and new potential combinations of technologies for advances in this emerging worldwide field and their uses. The review also relates the use of these six technologies in health conditions, health care, emotion recognition, occupancy, mobility, posture recognition, localization, fall detection, and generic activity recognition applications. The above can serve as a road map that allows readers to execute approachable projects and deploy applications in different socioeconomic contexts, and the possibility to establish networks with the community involved in this topic. This analysis shows that the research field in activity recognition accepts that specific goals cannot be achieved using one single hardware technology, but can be using joint solutions, this paper shows how such technology works in this regard.https://www.mdpi.com/1424-8220/20/15/4227smart homeAALambient assisted livingactivity recognitionhardwarereview |
| spellingShingle | Andres Sanchez-Comas Kåre Synnes Josef Hallberg Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies Sensors smart home AAL ambient assisted living activity recognition hardware review |
| title | Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies |
| title_full | Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies |
| title_fullStr | Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies |
| title_full_unstemmed | Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies |
| title_short | Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies |
| title_sort | hardware for recognition of human activities a review of smart home and aal related technologies |
| topic | smart home AAL ambient assisted living activity recognition hardware review |
| url | https://www.mdpi.com/1424-8220/20/15/4227 |
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