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

For green building, 'durable is the new 'sustainable'

Reducing the negative environmental impact of buildings—globally one of the largest contributors to greenhouse gas emissions—might be even more difficult than expected. New research from Drexel University indicates that, ...

Energy & Green Tech

Biosolar roof sets new standard for climate-resilient cities

A study of Bradfield City's First Building green roof confirms that combining native rooftop gardens with solar panels reduces urban heat, increases renewable energy generation and supports local biodiversity.

Hi Tech & Innovation

AI-powered system can predict how modern house fires behave

A team of researchers is harnessing artificial intelligence (AI), data science and advanced mathematics to better predict how fires behave in modern homes, work that could ultimately help save lives during emergencies.

Energy & Green Tech

Day-ahead solar forecasting improved for energy sector by up to 13%

Researchers from North Carolina State University have demonstrated techniques that can improve day-ahead solar forecasts by up to 13% over the most consistently performing individual model. The work also emphasizes the importance ...

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