Kevin Mayer

To reach net zero emissions by 2050, the International Energy Agency estimates that 20% of the existing buildings need to be renovated by 2030. However, assessing a building’s renovation potential today is a slow and costly process, as current methods generally require on-site visits of qualified experts or computationally expensive physical energy models, at times even a combination of both. To accelerate the decarbonization of the building sector, I propose an interdisciplinary approach which combines expertise in civil engineering with the scalability of data-driven algorithms and remote sensing. To do so, the proposed approach evaluates individual buildings in terms of their renovation potential by analyzing a property’s street view, aerial, LiDAR, and thermal infrared data in an automated fashion. If successful, this approach would enable policymakers, urban planners, building owners, and contractors to prioritize and target renovation efforts more efficiently.