How technology can support social landlords tackling fuel poverty
Leveraging sensor technology to provide greater visibility
One of the issues facing landlords is the lack of knowledge and transparency surrounding home energy use, residents don’t usually come forward and openly declare that they are in fuel poverty. Using the insights provided from IoT sensors and expert data analysis you can identify energy usage patterns, and the temperature inside and outside the property to better understand if the tenant is in need of support.
Pinpointing properties for speedier responses
Pinpointing properties requiring attention allows social housing providers to be more proactive in the management of their housing stock. Proactive intervention enables better targeting of resources, resolving property deficiencies more quickly, saving money and improving living conditions for tenants. Understanding an entire stock, looking to intervene early and finding direct solutions to each problem can all be achieved using iOpt’s solution, ensuring that already stretched resources are being used effectively.
Loreburn Housing Association takes a proactive approach
Glynis L. Morris, Head of Housing from Loreburn Housing Association mentioned the impact of iOpt’s innovative platform and expert analysis in tackling fuel poverty challenges.
“Two years ago, Loreburn Housing Association embraced iOpt's monitoring solution, recognising that technology is a valuable ally for our modest-sized team in efficiently managing our homes. As the Head of Housing, prioritising tenant welfare is paramount, and leveraging this solution has proven invaluable in our mission to combat fuel poverty. iOpt allows us to pinpoint tenants quietly grappling with the challenge of affording heating without voicing their struggles. This proactive approach enables us to identify those in need, ensuring no home remains unnoticed.”
Unique algorithms trained to predict fuel poverty
iOpt’s solution can detect fuel poverty in a home. Our algorithms have been trained over a number of years, across thousands of properties, meaning we can now actively predict those that will fall into fuel poverty.
Book a demonstration of our solution, and we will be able to provide you with a number of practical client use cases relating to this.