With the fast development of IoT sensors and other digital technologies, it is now possible to collect privacy-preserving health data from private dwellings and homes. The project aims to design and develop trustworthy IoT-based machine learning algorithms to leverage in-home behavioural data coupled with contextual data related to age group, ethnicity, etc., to provide a highly personalised approach to detecting and preventing adverse events, which would negatively affect the graceful and quality of in-home ageing. The aim is to accurately predict and prevent adverse health events using advanced and highly personalised techniques using non-obstructive and invisible technologies.
