RT info:eu-repo/semantics/article
T1 An unsupervised method to recognise human activity at home using non-intrusive sensors
A1 Gómez Ramos, Raúl
A1 Duque Domingo, Jaime
A1 Zalama Casanova, Eduardo
A1 Gómez García-Bermejo, Jaime
K1 Home automation
K1 Domótica
K1 Internet of things
K1 Internet de las cosas
K1 Internet - Tecnología
K1 Human activity recognition
K1 Hidden Markov models
K1 Voz - Informática
K1 Sensor networks
K1 Computer Communication Networks
K1 1203.17 Informática
K1 1203.25 Diseño de Sistemas Sensores
AB As people get older, living at home can expose them to potentially dangerous situations when performing everyday actions or simple tasks due to physical, sensory or cognitive limitations. This could compromise the residents’ health, a risk that in many cases could be reduced by early detection of the incidents. The present work focuses on the development of a system capable of detecting in real time the main activities of daily life that one or several people can perform at the same time inside their home. The proposed approach corresponds to an unsupervised learning method, which has a number of advantages, such as facilitating future replication or improving control and knowledge of the internal workings of the system. The final objective of this system is to facilitate the implementation of this method in a larger number of homes. The system is able to analyse the events provided by a network of non-intrusive sensors and the locations of the residents inside the home through a Bluetooth beacon network. The method is built upon an accurate combination of two hidden Markov models: one providing the rooms in which the residents are located and the other providing the activity the residents are carrying out. The method has been tested with the data provided by the public database SDHAR-HOME, providing accuracy results ranging from 86.78% to 91.68%. The approach presents an improvement over existing unsupervised learning methods as it is replicable for multiple users at the same time.
PB MDPI
SN 2079-9292
YR 2023
FD 2023
LK https://uvadoc.uva.es/handle/10324/67137
UL https://uvadoc.uva.es/handle/10324/67137
LA eng
NO Electronics, 2023, Vol. 12, Nº. 23, 4772
NO Producción Científica
DS UVaDOC
RD 17-may-2024