America has an infrastructure problem. Nearly half of U.S. public roads are in poor or mediocre condition. Almost 250,000 bridges across the country will need to be replaced in the next two decades. And a quarter of U.S. GDP relies on five cities that all face extreme weather risks.
The dramatic collapse of Baltimore’s Francis Scott Key bridge earlier this year was a stark reminder that some of the U.S.’s most critical pieces of infrastructure are also the most vulnerable. It took months for Maryland’s government to fully reopen the port; the bridge itself will take years to repair.
More recently, a flood in the Queens-Midtown tunnel—caused by human error from a crew working nearby—temporarily closed one of the busiest throughways in a city that nearly 1 million people commute into every day.
Doing nothing would be costly, both financially and in terms of public safety. Yet the truth is that the U.S. simply does not have enough labor, resources, or materials needed to prepare its infrastructure for an uncertain future affected by climate change.
Business leaders are hyping up AI for how it might transform the digital world. But they’re only now beginning to understand the enormous effect it can have on the physical world. AI can help us design, build, and re-build the U.S.’s many roads, bridges, factories, homes, and cities, ahead of a rapidly changing future.
Take sustainability. The construction industry is one of the world’s most wasteful sectors, responsible for nearly 40% of global carbon emissions.
Yet it sits on vast amounts of data that can help with sustainability. Typically, 95% of data captured in construction goes unused. That includes everything from material usage and sourcing information to energy consumption metrics, transportation logistics, and even waste production during the building process.
AI can analyze this data and improve decision-making on material use and energy consumption, cutting down on project waste.
One example from our own work is our partnership with MBH Architects and FactoryOS on Project Phoenix, an affordable housing development in West Oakland, Calif. We reduced time, cost, and carbon footprint by almost half compared to traditional housing in the San Francisco Bay Area, thanks to AI-optimized reductions in construction waste.
Projects also involve multiple models from architects, engineers, city planners, manufacturers, designers, and construction workers. AI can facilitate communications across these often massive and complicated endeavors.
Connected data helped optimize the transformation of San Diego International Airport’s Terminal 1, by allowing every stakeholder on the complicated construction project to submit and access data on a shared platform.