AI could flag issues with Cambridgeshire council homes before ‘potential crisis hits’

The tool will scan data from thousands of properties and flag the ones most likely to deteriorate

Artificial Intelligence (AI) could be used to flag issues with council homes before “potential crisis hits”. Researchers at the University of Cambridge are developing a new AI tool alongside Cambridge City Council and South Cambridgeshire District Council.

It will scan data from thousands of properties and flag the ones most likely to deteriorate, as well as the residents “most likely” to be harmed. According to the university, the tool will combine three sources of data into a single risk score for each property.

The first source is satellite data and it includes systems that can detect heat loss from buildings using thermal imagery captured by satellites. The second source is conventional housing data such as construction type, Energy Performance Certificate (EPC) ratings, records of damp and mould, and repair histories.

The third source is what the researchers called ‘soft’ data including fuel poverty indicators, rent arrears, and accumulated logs of tenant contacts that councils already hold.

Researchers said the data, on a dashboard, would display a map of “risk hotspots”. They said it would not just flag buildings in poor condition, but highlight “where a vulnerable person lives in one”.

Head of housing at South Cambridgeshire District Council Peter Campbell said “at the moment we’re very much waiting for things to break before we act”. He believes that better data could make teams more efficient.

He added: “Quite often when things break, it’s not only the item itself that gets damaged, but also the damage caused by the break. For example, it’s not just the roof that needs replacing; it’s where the water has gotten in and damaged the rest of the property.”

“What we’re doing now is identifying people with whom we’ve had absolutely no contact and prioritising them for a home visit,” Mr Campbell continued. “But we don’t have the resources to do that for everybody, all the time.”

The researchers said that the project, called Predictive Risk Intelligence for Social housing Maintenance (PRISM) is not designed to make automated decisions about people’s homes or welfare. All alerts generated by the model would be reviewed by housing officers.

The project is designed as a proof of concept over 12 months. If it works, both councils said they hope it could serve as a template for social housing authorities elsewhere in the UK.

The system is being developed by Professor Ronita Bardhan and Dr Ramit Debnath from Cambridge’s Department of Architecture and the Centre for Human-Inspired AI (CHIA). Professor Bardhan said that “this is just a starting point”, but they hope “it can be replicated across different councils across the country”.