@inproceedings{dc11757454944fa290b977b505be6c81,
title = "Aged care act compliance, roughness index, edge intelligence and an optimised process",
abstract = "Aged and healthcare environments are the focus of our research. We address current needs for an optimised process to meet legislative and quality requirements of the Aged Care Act 2024. We developed inference model-based microcontroller sensor clusters to deliver operational data and confirm the delivery and quality of scheduled care. Our research observations have devised the right mix of environmental and activity-based sensing to meet the heightened situational awareness required by the Act. We enhance workflow effectiveness by improving actionable intelligence. We use ML-Trained micro controller devices with onboard sensors to deliver real-Time operational guidance and optimised health care processes.",
author = "Ollencio D'Souza and Subhas Mukhopadhyay and Sheng, {Quan Z.}",
year = "2024",
doi = "10.1109/ICST62759.2024.10992220",
language = "English",
isbn = "9798350374834",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "127--132",
booktitle = "2024 17th International Conference on Sensing Technology (ICST)",
address = "United States",
note = "17th International Conference on Sensing Technology, ICST 2024 ; Conference date: 09-12-2024 Through 11-12-2024",
}