JUNO Project: deployment and validation of a low-cost cloud-based robotic platform for reliable smart navigation and natural interaction with humans in an Elderly Institution
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Pavón Pulido, Nieves; Blasco García, Jesús Damián; López Riquelme, Juan Antonio; Feliu Batlle, Jorge Juan; Oterino Bono, Roberto; [et al.]Área de conocimiento
Ingeniería de Sistemas y AutomáticaPatrocinadores
This research was funded by Fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia, grant number 21668/PDC/21 and grant number 21593/FPI/21, provided by the same funding institution.Fecha de publicación
2023-01-02Editorial
MDPICita bibliográfica
Pavón-Pulido, N.; Blasco-García, J.D.; López-Riquelme, J.A.; Feliu-Batlle, J.; Oterino-Bono, R.; Herrero, M.T. JUNO Project: Deployment and Validation of a Low-Cost Cloud-Based Robotic Platform for Reliable Smart Navigation and Natural Interaction with Humans in an Elderly Institution. Sensors 2023, 23, 483. https://doi.org/10.3390/s23010483Revisión por pares
siPalabras clave
smart assistant robotshuman–robot natural interaction
autonomous navigation
digital transformation of health systems
Resumen
This paper describes the main results of the JUNO project, a proof of concept developed in
the Region of Murcia in Spain, where a smart assistant robot with capabilities for smart navigation
and natural human interaction has been developed and deployed, and it is being validated in an
elderly institution with real elderly users. The robot is focused on helping people carry out cognitive
stimulation exercises and other entertainment activities since it can detect and recognize people, safely
navigate through the residence, and acquire information about attention while users are doing the
mentioned exercises. All the information could be shared through the Cloud, if needed, and health
professionals, caregivers and relatives could access such information by considering the highest
standards of privacy required in these environments. Several tests have been performed to validate
the system, which combines classic techniques and new Deep Learning-based methods to carry out
the ...
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