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How can machine learning help prioritize building energy retrofits?

How can machine learning help prioritize building energy retrofits?

In a recent study, our partner Technische Universität Berlin (Sustainability Economics of Human Settlements) – TUB looked at 25 million buildings in France, Spain and the Netherlands and tried to estimate the construction year and retrofit need. The overarching goal was to assess if machine learning methods can facilitate the identification of retrofit candidates at scale.

New mobility and the circular economy

New mobility and the circular economy

Recent years have seen the rapid increase of micro e-mobility ownership and the launch of public rental schemes across many European cities. However, its long-term impact is dependent on its ability to complement other sustainable modes, and ultimately to displace car use and ownership.

Construction automation – a recipe for reduced GHG emissions?

Construction automation – a recipe for reduced GHG emissions?

The CircEUlar project has an emphasis on GHG reductions: Oxford islooking at how BIM can help. It is apparent that the benefits for small architects and constructors, working (for example) on single home projects with a single contractor, may be limited, and in addition they may not have the resources to devote to its implementation.