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IoT-Based Human Fall Detection System.
- Source :
- Electronics (2079-9292); Feb2022, Vol. 11 Issue 4, p592, 1p
- Publication Year :
- 2022
-
Abstract
- Human falls are an issue that especially affects elderly people, resulting in permanent disabilities or even in the person's death. Preventing human falls is a social desire, but it is almost impossible to achieve because it is not possible to ensure full prevention. A possible solution is the detection of human falls in near real-time so that help can quickly be provided. This has the potential to greatly reduce the severity of the fall in long-term health consequences. This work proposes a solution based on the internet of things devices installed in people's homes. The proposed non-wearable solution is non-intrusive and can be deployed not only in homes but also in hospitals, rehabilitation facilities, and elderly homes. The solution uses a three-layered computation architecture composed of edge, fog, and cloud. A mathematical model using the Morlet wavelet and an artificial intelligence model using artificial neural networks are used for human fall classification; both approaches are compared. The results showed that the combination of both models is possible and brings benefits to the system, achieving an accuracy of 92.5% without false negatives. [ABSTRACT FROM AUTHOR]
- Subjects :
- ARTIFICIAL neural networks
OLDER people
ARTIFICIAL intelligence
INTERNET of things
Subjects
Details
- Language :
- English
- ISSN :
- 20799292
- Volume :
- 11
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Electronics (2079-9292)
- Publication Type :
- Academic Journal
- Accession number :
- 155709389
- Full Text :
- https://doi.org/10.3390/electronics11040592