Homeara+ will integrate machine learning (ML) to augment the efforts of nurses and support workers by identifying behavioural changes based on sensor data. This enables timely, targeted interventions while minimising false alerts, helping care teams focus where they are needed and reducing preventable hospitalisations.
The system will be trialled in partnership with Suncare Community Services, a regional aged care provider. Built using a Design Thinking approach, Homeara+ reflects insights from users, ensuring the system is practical and accessible. This strong user-centred foundation ensures that the integration of ML is technically sound and aligns with the workflows and needs of real-world home care settings. To support implementation, the project will produce a Homeara+ Implementation Toolkit, offering practical guidance on ML-enhanced monitoring and dashboard interpretation. Structured training will also be delivered to home care staff, clients, and families. By embedding ML to augment aged care delivery, this project establishes a scalable model that strengthens workforce capability and supports sustainable, technology-enabled care for older Australians ageing in place.
"This grant enables the Homeara Research Collective’s multidisciplinary team to advance new "Smart" models of home care that reflect older Australians’ desire to age in place, respond to critical workforce challenges, address monitoring health in more rural and remote areas, and provide peace of mind to families. By integrating machine learning into sensor-enabled home monitoring, Homeara+ will deliver scalable, nurse-led innovations that strengthen the quality, responsiveness, and sustainability of aged care in a variety of and home settings."
Dana, Academic Lead Healthy Ageing Gympie/ Senior Lecturer; A/Prof Rania Shibl, Technology Discipline Lead; Senior Lecturer Dr Gordana Dermody at University of the Sunshine Coast