WattScale is an open source AI tool that identifies energy-wasting homes

Researchers at the University of Pittsburgh, University of Massachusetts Amherst, and Microsoft Research India have developed a system -- WattScale -- that leverages AI to pick out the least energy-efficient buildings from a city- or region-level population. In a preprint study, they used it to show that half of the buildings in a 10,000-building data set were inefficient, in large part due to poor construction. They also emit over a third of the nation's greenhouse gases, which is more than any other sector of the economy. Solving for the disparity requires identifying buildings that are the least efficient and thus have the greatest need for improvements, but approaches that rely on the age of a building or its total energy bill don't work well; greater energy usage doesn't necessarily point to inefficiencies. WattScale aims to address this with (1) a Bayesian modeling technique that captures variable distributions governing the energy usage of a building and (2) a fault analysis algorithm that makes use of these distributions to report probable causes of inefficiency.