Focus resources where they are most needed with our address-level predictions for health risks in homes.
Available exclusively to our Portfolio and Pathways clients, this machine learning module predicts the likelihood of main health hazards across the housing stock to focus investment in energy efficiency, public health and stock condition improvements.
Our Portfolio and Pathways services identify the likelihood of Excess Cold, but our clients want to know more about other health risks in their housing stock. This service identifies health risks in housing by layering stock condition data from monitoring and surveys with the Portfolio or Pathways data, and applying machine learning and statistical predictions over the combined datasets.
The service currently predicts – at address level – the likelihood of: damp or cold; fires, electrical hazards, risks from Carbon Monoxide or poisoning from other fuel combustion and risks from falls inside or around a property at address level.