Page 6: Research news on AI in built environment

AI in the built environment encompasses data-driven and physics-informed methods to model, predict, and optimize the performance and resilience of buildings and infrastructure. Machine learning and advanced simulation are applied to building energy use, HVAC control, and solar and wind power forecasting, as well as to hazard-related phenomena such as subsidence, floods, fire, and seismic events. The field also integrates retrofitting strategies, climate-smart housing design, and regulatory considerations to enhance energy efficiency, comfort, and disaster resilience in urban systems.

Computer Sciences

RiverMamba: New AI architecture improves flood forecasting

Extreme weather events such as heavy rain and flooding pose growing challenges for early warning systems worldwide. Researchers at the University Bonn, the Forschungszentrum Jülich (FZJ), and the Lamarr Institute for Machine ...

Energy & Green Tech

Making it easier to recycle your house

According to Statistics Norway, an average of approximately 1,100 detached houses have been demolished each year in Norway over the course of the past decade. However, only 7% of the wood from these buildings was recycled.

Energy & Green Tech

Two AI methods can improve wind speed predictions for wind farms

Last year, wind energy accounted for 23.2% of all energy injected into the Spanish electricity system, according to data published by Red Eléctrica in its latest 2024 report. Although wind power leads national energy production, ...

Engineering

Climate-smart housing design helps cities beat the heat

Painting walls in light colors, insulating roofs, choosing medium-sized windows, and aligning buildings to the sun's path may seem like simple choices. But they could provide powerful defenses against climate change for millions ...

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