Trials to monitor smart meter data in elderly care

Written by Jenni Davidson on 20 April 2021 in News

Scottish institutions to work with consenting older citizens to track energy usage

Credit: PA

Smart meters are being trialled as a form of remote monitoring to flag up possible causes for concern for elderly and disabled people living in their own homes. 

The trial is being led by the University of Edinburgh’s School of Informatics in partnership housing provider Blackwood Homes and Care and The Data Lab, a national innovation centre backed by the Scottish Government.

Through the Smart Meters for Independent Living (SMILE) project the group are developing and testing artificial intelligence  methods to analyse energy usage data from consenting residents’ smart meters, creating a view of their daily routines and spotting unusual changes in behaviour that might indicate problems. 

The trial began in November 2019 and is currently analysing energy usage data in several homes across Scotland. The system works by machine learning algorithms using energy-usage patterns to identify the timing of people's relevant activities in the home and looking for changes that should be flagged up.

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

Individuals and their families or carers can set specific rules for the system, telling it which changes in routine are a cause for concern, such as a shower lasting longer than usual or a change to normal cooking schedules, which could indicate that an incident has occurred. The aim is for the new predictive digital technology will provide an additional service to complement the traditional 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.

The technology also has the potential to be used as a decision support tool, so that if it detects a resident getting up frequently during the night, health and care professionals can review whether they need changes in their support.

The project is also supported by CareBuilder, Hildebrand, Mydex CIC & Smart Energy GB. Findings of the trial are expected to be published in autumn 2021.

Colin Foskett, head of innovation at Blackwood Homes, said: ““If we can prove the principle of the technology with this project, then we have an opportunity to provide a safety net for vulnerable people, to identify patterns of decline and provide early intervention, potentially saving lives and reducing hospital admissions.”

Gillian Docherty, CEO 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. Scotland has an aging population, and in the next few decades we need to find new ways to deliver the best possible social care against a backdrop of stretched resources and falling carer numbers. Machine learning and AI can be a non-invasive way to do this and will also encourage greater personalisation of care based on an individual’s data.”


About the author

Jenni Davidson is a journalist at PublicTechnology sister publication Holyrood, where a version of this story first appeared. She tweets as @HolyroodJenni.


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