CHANGES in patterns of smart meter usage could help alert carers to health-related incidents around the home.

The Smart Meters for Independent Living project will see a consortium develop and test machine learning and artificial intelligence (AI) methods to analyse energy usage data from consenting residents’ smart meters, creating a view of their daily routines and spotting unusual changes in behaviour which could cause concern.

The technology system is being piloted in a ground-breaking trial led by The University of Edinburgh’s School of Informatics, in partnership with housing care specialist Blackwood Homes and Care, which provides a range of accessible housing for people with disabilities and older people, and Scottish Innovation Centre, The Data Lab.

Individuals and their loved ones or carers can set specific “rules” for the system, telling it which changes in routine are a cause for concern, such as the duration of a shower being longer than usual, or a change to normal cooking schedules, which could indicate that an incident has occurred.

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Machine learning algorithms use energy usage patterns to identify the timing of people’s relevant activities in the home, looking for changes that should be flagged up.

The system will then alert the individual, their loved one or carer, enabling a decision on the best course of action to be made.

The ambition is that the new predictive digital technology will provide an additional service to complement the traditional proactive push button personal alarm worn by residents, particularly aiding people with dementia and those who may be confused, may forget or be unable to activate their current alarm.

Gillian Docherty, chief executive of The Data Lab, said: “This project has the potential to shape the way we view machine learning and AI in social care settings, by empowering individuals to go about their daily routines without worry and only receive carer intervention when necessary.”