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Published VersionCC BY-NC-ND V4.0, Open Access
Journal article
Design of a shared context-aware assistive robot for personalised aged-care services
Digital Medicine, Vol.10(1), pp.1-11
2024
Abstract
Background:
Sensors, robotics, the Internet of Things (IoT) and data analytics hold considerable potential for enhancing the efficiency of care and health outcomes in the health and aged care sectors. The Australian aged care sector in particular faces significant challenges due to an aging population and outdated technological infrastructure. This article builds upon the foundational research conducted through the collaboration between the University of New South Wales and the University of the Sunshine Coast, as part of the European Union VictoryaHome (VH) project (2014–2016). The VH project, which involved partners from Australia, Norway, Sweden, the Netherlands, and Portugal, aimed to enhance the emotional well-being and security of elderly individuals in their homes. The present study specifically addresses some of the challenges identified in relation to the prohibitively high costs and usability of robots for personalized services in the aged care sector.
Methods:
This paper presents the design and implementation of an affordable service robot specifically developed to offer personalized services to multiple users in aged care facilities. The system utilizes a Raspberry Pi 4 and incorporates functionalities that are tailored to the needs identified through interviews with facility managers and staff.
Results:
We successfully demonstrate tracking of entities within a room-scale environment and the switching of profiles using cost-effective devices. Moreover, by tracking multiple entities simultaneously we were able to achieve powerful context-aware functionality that was seamless to the end-user.
Conclusion:
This study underscores the feasibility and potential benefits of employing low-cost, context-aware service robots in aged care environments.
Details
- Title
- Design of a shared context-aware assistive robot for personalised aged-care services
- Authors
- Nicholas Duthie - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringKeyvan Ansari - Murdoch UniversityMingzhong Wang - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringPradeep Kumar Ray - Shanghai Jiao Tong University
- Publication details
- Digital Medicine, Vol.10(1), pp.1-11
- Publisher
- Wolters Kluwer - Medknow Publications and Media Pvt. Ltd.
- Date published
- 2024
- DOI
- 10.1097/DM-2023-00017
- ISSN
- 2226-8561; 2542-629X
- Copyright note
- This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0, where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially.
- Data Availability
- Not applicable.
- Organisation Unit
- Healthy Ageing Research Cluster; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991014497502621
- Output Type
- Journal article
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