Designing sustainably with machine learning
Some architects may look towards machine learning (ML) powered tools to reduce construction costs, time and waste. Emerging design tools that utilize AI often leverage a a subset called machine learning which uses models and algorithms to generate insights and support smarter design decisions. “For example, using ML-powered tools, an architect can rotate a building 10 degrees and instantly see how that change impacts thermal performance,’ said Dan Ring, Senior machine learning team lead at Chaos. “This early insight helps pinpoint potential pain points and optimise energy efficiency before breaking ground.”
With the ML powered assistance teams have the ability to identify issues earlier in the process than expected. This can help minimise redesigns, reduce the amount of material waste during construction and contribute to a more efficient construction process. ML is also used to do easy but time consuming tasks, allowing for more time for an architect to be more creative.
“Machine learning doesn’t just improve design outcomes; it makes sustainable construction more affordable and accessible,” said Ring. “By streamlining workflows and cutting iteration time, these tools can reduce design and construction costs, empowering architects and developers to bring sustainable design to more communities.”
