AI for the Construction Industry

AI for the Construction Industry

Fifteen per cent of the world’s carbon emissions come from heating and cooling buildings, which means AI has a key role to play—from automating tasks to optimizing resource allocation.

“Even though the HVAC systems in buildings is not the most exciting topic in the world, it accounts for just a huge amount of energy consumption on our planet. So that turns it into a climate problem we have to face,” said Sam Ramadori, CEO of BrainBox AI, a company that uses AI to make buildings smarter and greener.

The world is moving toward renewable energy. The problem is, said Ramadori, when renewable energy starts becoming an important part of your total energy mix, you start running into problems with intermittency—like relying on sunshine for solar power. That intermittency requires more flexibility in how we use energy.

BrainBox AI connects to a building’s HVAC system and sends real-time optimized control commands to minimize emissions and energy consumption based on weather, utility data and grid emissions.

The next step is to connect hundreds or even thousands of buildings and help them react to the needs of the grid. So if the grid is under stress, AI-enabled buildings could start cooperating with each other and reducing peak energy consumption at that moment in time. “So for us, that’s what comes next,” said Ramadori.

Another area where AI has huge potential is in pre-construction. Projects can take two, three or even four years to complete and, subsequently, collect data on key performance indicators—which makes it difficult to estimate costs for new projects.

“We did a proof of concept three years ago to see if AI could help us predict costs, more as a tool to guide us as estimators,” said Sean Boyer, VP of pre-construction with Pomerleau.

Historical data from previous projects can be processed by AI in a matter of hours, helping estimators during bid preparation, and schedulers can use predictive models for more accurate time estimations. But confidence in these results depends on the quality of the data. 

“That’s probably one of the biggest issues is getting all your data standardized,” said Boyer.

While no construction project is the same, AI is coming to the fore in areas such as predictive analytics, autonomous construction vehicles, health and safety, quality control and sustainability.

“There was traditionally a fear that AI would take people’s jobs,” said Brandon Milner, SVP of digital and data engineering with EllisDon.

But now people are seeing how AI could augment their jobs; for example, a safety engineer could use AI for fault detection and predictive maintenance. “These are the things that will start to change and evolve and accelerate the industry,” said Milner.

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