Page 5: 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.

Engineering

New model tests hundreds of MTA subway flood defenses in one minute

As transit agencies face growing climate risks and limited capital budgets, deciding which flood protection measures to implement—and where—has become a critical challenge. Now, a research team at NYU Tandon School of Engineering ...

Energy & Green Tech

AI tool predicts building emissions from simple text descriptions

Researchers at the University of Bath have developed the first artificial intelligence (AI) tool that predicts the carbon footprint of buildings from simple text descriptions, giving architects real-time feedback on sustainability ...

Engineering

City skylines need an upgrade in the face of climate stress

When structural engineers design a building, they aren't just stacking floors; they are calculating how to win a complex battle against nature. Every building is built to withstand a specific "budget" of environmental stress—the ...

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