A new AI-powered device could help identify when older or vulnerable people living alone may need immediate medical support.
Developed by CENSIS, the University of Edinburgh, Blackwood Homes and Care, and Amsterdam-based Carebuilder, the technology is being trialled across 19 households in Glasgow Dundee, and Buckie.
Linked wirelessly to a smart meter or conventional electric meter, the device disaggregates data to identify certain high-power electrical items within the home – such as microwaves, electric showers, and kettles. Using machine learning, it can determine when such devices have been switched on and off – and, most importantly, spot any anomalies.
The partners explained that, if a person usually wakes up and boils a kettle to make tea by 8am, the monitoring device will identify this as normal behaviour. However, if the kettle has not been used by 9am, an automated text will be sent to the householder and then to a family member, carer, neighbour, or a response service.
Stephen Milne, director of strategic projects at CENSIS, said,“This project is all about repurposing energy data to help inform social care and supporting healthy aging. The system learns the typical activity of the individual living in the household and then spots any erratic behaviour, helping to identify when they may have issues.
“These could be one-off events, like a fall, and with further research, the system may be able to track changes over a longer time period that may indicate gradual, and more difficult to spot health issues, such as the onset of a condition such as dementia.
“While there are other technologies related to monitoring activity, this is the first full service deployment that has been implemented through passively monitoring a property’s smart meter system. The device can also pick out each item being monitored, making it much more likely to spot any anomalies, and is barely noticeable for the householder.
“After these trials, we are looking to develop the technology to the commercial product stage and deploy it at a much bigger scale, and are open to taking this forward with talks with potential long-term partners.”
Lynda Webb, senior researcher in the school of informatics at the University of Edinburgh, added, “The idea of monitoring electricity use in the home, for spotting if a person might need help, was first conceptualised 10 years ago. A prior project of 250 homes in Edinburgh enabled the development of the algorithms that are used today in this project. It is so exciting to see the application of this idea and the years of algorithm development becoming a service which is already impacting the lives of people in the trial.”
Blackwood Homes and Care’s three-year Peoplehood project aims to develop a future-proof model for independent living for its residents, allowing people to live healthier and happier for longer. Through a series of initiatives, it will set out a blueprint for welcoming communities with age-friendly homes, supported by cutting-edge technologies, making independent living achievable and sustainable as people grow older.
Lindley Kirkpatrick, peoplehood programme manager at Blackwood Homes, commented, “The Peoplehood project has focused on developing activities, techniques and technologies and we are delighted with the progress that has been made across several fronts.
“The development of this new device utilising AI technology could, however, prove to be one of the most exciting that we have seen. For carers and loved ones to get ahead of time notice of potential medical emergencies as well as the onset of conditions of dementia is of huge importance.
“We very much look forward to examining the details that come out of the trial to understand how this has aided participants of the Peoplehood project.”
