Albyn Housing Fit Homes

Finalist category: Connected Society Award


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Connected Society Award, Finalist, 2019

 In 2008 an Albyn Housing Society tenant was found dead at home, having lain undiscovered for 14 months. Vowing to learn valuable lessons, Albyn commissioned research to identify a solution that would not only prevent this from happening again, but help address the pressures caused by Scotland’s aging population. 


Working with a modular construction expert and NHS Highland, the Albyn Housing Society-led partnership developed a new housing concept that hosts various sensors, enabling the capture of data and predictive health analytics. Built of modular construction, the ‘Fit Home’ hosts various levels of sensoring equipment enabling the capture of data and associated predictive health analytics which could potentially help prevent episodes or events leading to ill health. It will also include flexible spaces and walls for storing medical equipment.  


Developed through co-design with partners, potential tenants, health and care professionals, young people and enterprise experts, it will provide the solution Albyn originally sought whilst enabling the NHS to support more people at home. Thus including the potential to prevent hospital admissions and enable hospital discharge. 

The central concept of these high-quality, sustainable homes is that they will include ambient, physiological and building sensors to collect data that can be monitored and responded to by a variety of agencies – potentially transforming the way health and social care is delivered. Falls in particular are of great concern to vulnerable residents, their families and the health and care sector. By looking at data surrounding areas such as dehydration, diet, the use of certain prescribed medication and levels of activity and social interaction, the partnership hopes to develop a means of using digital technology to enable families and agencies to intervene with preventative measures before incidents can occur. This could transform countless lives as populations across the globe continue to grow older. 


The technology builds on two leading-edge Artificial Intelligence technologies: recognising human activities from real-time sensor data, and understanding these activity profiles to find similarities with the behaviour of other people and to recognise changes in activity patterns. Alerts to the resident/family or healthcare professionals will be based on activity profiles and so are backed up by evidence from real-life behaviour. The system will learn from known precursors of falls but will also be able to discover new indicators of risk of falling.  

 This new housing concept will give people the opportunity to live at home for longer in houses that are adapted to suit individual needs and lifestyles. In addition, it is hoped early regular health monitoring and the benefits of early intervention will reduce the need for long hospital and care home stays, allowing people to continue to live independently in their community. In the longer term, this project will contribute to low carbon efficiency as the new homes will have efficient, low cost heating, powered from sustainable sources. In addition, with falls costing NHS Scotland £471million a year, there is potential for substantial economic benefit to health and social care services as well as significant direct commercial return through sale or licensing of the product. 


The pilot phase is now complete, and homes have all been allocated in partnership with the NHS and the Highland Council. The team are now preparing to roll out further Fit Home test beds to include housing partners and tenants which will include retrofitting the technology into existing homes. They will also be developing their next algorithm around cardiovascular health – working with the British Heart Foundation to identify markers that signal when someone is potentially at risk of having a stroke or heart attack. As well as working with GP’s to develop a means of sharing changes in participants’ wellbeing without requiring individuals to wear technology. 

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