A predictive artificial intelligence (AI) tool is being developed by Cambridge authorities to support more efficient maintenance action for social housing tenants.
The PRISM (Predictive Risk Intelligence for Social housing Maintenance) project is designed to identify council properties with the highest risk of deterioration, while also determining which tenants are most likely to experience harm if the property is damaged.
Led by researchers at the University of Cambridge, Cambridge City Council, and South Cambridgeshire District Council, the initiative will involve the analysis of data about properties and to help predict issues before residents report them.
Peter Campbell, Head of Housing at South Cambridgeshire District Council, said: ‘At the moment we’re very much waiting for things to break before we act’.
‘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’, he explained.
With both local authorities managing thousands of properties collectively, the improved data is expected to increase the efficiency of operations across council areas.
Professor Ronita Bardhan and Dr Ramit Debnath from Cambridge’s Department of Architecture and the Centre for Human-Inspired AI (CHIA) are developing the system, which integrates satellite data, conventional housing data, and ‘soft’ data to provide a ‘map of risk hotspots’.
This ensures that the computer signals to both deteriorating buildings, as well as where vulnerable residents are living in these properties.
‘The interesting bit, which is unique to this project, is that we’re predicting not just on observation data, but also on data from lived experience’, said Dr Debnath.
Mr Campbell commented: ‘What we’re doing now is identifying people with whom we’ve had absolutely no contact and prioritising them for a home visit’, but added that they ‘don’t have the resources to do that for everybody, all the time’.
The proof of concept project will span a 12-month period, with the aspiration for it to be used by other UK social housing authorities if successful.
