Using Advanced IoT-based Machine Learning for In-Home Quality Ageing

  • Bouguettaya, Athman (Chief Investigator)
  • Liu, Tongliang (Chief Investigator)
  • Liu, Na (Chief Investigator)
  • Low, Lee Fay (Chief Investigator)
  • Sheng, Michael (Primary Chief Investigator)
  • Waller, Jason (Partner Investigator)

Project: Research

Project Details

Description

Trustworthy IoT-based machine learning algorithms will be developed to leverage in-home behavioural data that is coupled with contextual data related to age group, ethnicity, and other parameters to provide a highly personalised detection and prevention of adverse events that negatively affect the quality of in-home ageing. Presently the InteliCare system is reactive. Our research will enable to accurately predict and prevent adverse health events, using advanced and highly personalised techniques using non-obstructive and invisible technologies. We will use passive sensors, which will be complemented with contextual data to provide personalised detection and prevention of adverse health events
Short titleNSW Smart Sensing Network,USYD Led
StatusFinished
Effective start/end date1/08/2130/06/22