Robotics & Innovation has reported that the Quebec Wood Export Bureau (QWEB), a non-profit organisation for wood product manufacturers in Canada, has developed with global AI consultancy Brainpool.ai a machine learning tool which calculates the impact of CO2 in choices of early-phase building design.
According to QWEB and Brainpool.ai, the aim of the tool, CarbonFixer, is to help the building and construction industry decarbonise by showing how much CO2 is emitted in their design-related choices of using traditional concrete and steel in comparative scenarios with wood and bio-sourced building materials.
The building industry alone is responsible for 38% of the total global energy-related CO2 emissions, mainly due to the use of steel and concrete, with concrete alone accounting for 8%. The partnership between QWEB and Brainpool.ai hence aims to decarbonise the industry with this tool, to explore carbon-neutral alternatives of building materials.
QWEB’s US architect liaison and software project lead Eli Gould has described CarbonFixer as “like using a mortgage calculator before going to the bank, it gives an idea of what to expect.” Architects and sustainability professionals can feed the tool basic building data, such as dimensions, area and structural data, to produce scenarios that compare the use of steel, concrete or timber. It also has pre-sets for fire resistance and acoustics, and offers design considerations with industry-specific knowledge and norm.
“Attitudes to using wood in construction are changing,” said Gould. “We wanted to build a tool that counters the greenwashing around non-sustainable building materials and gives architects and construction firms the data and confidence to explore timber options.
“The Brainpool.ai team has been instrumental in developing the CarbonFixer, they were fast and passionate and have created something very robust that we can soon launch to market.”
Co-founder and managing director of Brainpool.ai, Kasia Borowska, also commented: “CarbonFixer is a complex application because of the volume of data that has to be collected. Our team of backend developers and ML experts collated the data quickly and built a robust proof-of-concept for the application, which the CarbonFixer team can develop further into the future. The project shows how environmental AI has a growing role in the construction industry from proving how sustainability is feasible, through to automating building designs to find the most eco-efficient plans.”
Robotics & Innovation explained that the final version of the tool will incorporate a machine learning engine which will continuously improve the accuracy of calculations and inputs. Future plans include integrations with popular design software, and a bank of archetype structures ready to be used and customised by design studios.
Source: Robotics & Innovation
