Page 10: 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

Architecture's past holds the key to sustainable future

Modern "sustainable"' innovations in architecture are failing to slow climate change, but revisiting ancient knowledge and techniques found in traditional architecture could offer better solutions.

Consumer & Gadgets

Living differently can help reduce your home's carbon footprint

An EPFL study has measured the carbon footprint of 20,000 residential buildings in Vaud Canton in Switzerland. The authors' findings show that a targeted approach will be key to lowering the emissions associated with residential ...

Energy & Green Tech

Cross-effects of behavioral strategies on household resource use

A small nudge can have a big impact. A study published in the Journal of Environmental Economics and Management and led by CMCC researcher Jacopo Bonan demonstrates that a "nudge"—a behavioral intervention based on personalized ...

Engineering

Building energy model offers cities decarbonization roadmap

A new software tool developed by Cornell researchers can model a small city's building energy use within minutes on a standard laptop, then run simulations to help policymakers prioritize the most cost-effective approaches ...

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