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
Over the past two decades, Haiti has endured the devastation of two catastrophic earthquakes—first in 2010 and again in 2021. Each disaster left behind widespread destruction: buildings reduced to rubble, entire communities ...
Mar 18, 2025
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Engineering
Agrivoltaic systems, which combine solar power generation with agricultural practices, offer a promising solution to the growing demand for both renewable energy and food production. By integrating solar panels with crops, ...
Mar 14, 2025
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Engineering
A researcher from VUB has developed a system that can predict wind turbine failures caused by early component malfunctions. He specializes in condition monitoring, a technique that uses data from turbine sensors and artificial ...
Mar 14, 2025
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