Temperature and Moisture

Temperature and Moisture – Impact on Social Housing

In 2019 we put our small sensors into social housing tenants homes in Leeds and York and gave the households our app.
We wanted to collect data about the home, calculate thermal performance and the effect on fuel usage, impact on health and wellbeing, likelihood of mould and damp, and the need for repairs. The app provided a ‘lived experience’ way to collect data from the tenant so we could adjust the conclusions and predictions.

We wanted to prove that given the right data served up in a format that people could understand, they would trust the information more and be more inclined to make small behaviour changes to improve their environment. We discovered that whereas the prediction algorithms to indicate problems with the property were accurate, people’s perception of comfort varied if you were young, old, had underlying health conditions, were active, lived in areas of economic deprivation.
In some instances, the algorithms told us that the home had cold, overheating or damp problems, but the tenants said that they found the environments comfortable or had simply learned to live with it as they found it hard to pinpoint the problem. In other instances we were able to identify habits that were affecting the performance of the home and for many of the tenants, it was the first time they understood how their actions impacted their home environment and the things they do to improve it.

We created our own firmware using standard sensor technology to get as much raw and calculated data at the edge at as low a cost as we possibly could. When you get down to the bit level, you kind of go ultra geeky, but having high resolution low cost data made it easier for us to create user experiences for all age, digital skill, accessibility and income levels.

We are continuing the work and planning new projects to create even deeper knowledge for communities. We want to thank the tenants, social care teams, charities, council workers and community health groups who helped us tackle a complex topic and guided the solutions. The journey to explainable AI for social good starts with them.

If you are a charity wanting to understand the impact of fuel poverty or a council who wants to understand the performance of their property portfolio, then get in touch.