Artificial Intelligence Steps In to Lower Carbon Footprint of Buildings

Artificial intelligence is starting to help buildings go greener.

Keeping our buildings running contributed roughly 26% of global energy-related greenhouse-gas emissions in 2022, according to the International Energy Agency. For the world to reach net-zero emissions by 2050, the agency says the energy that these buildings consume per square meter (around 11 square feet) needs to decline by around 35% by 2030.

Developers and construction companies have pursued more-efficient energy use in buildings over the past couple of decades. Leadership in Energy and Environmental Design, or LEED, certifications are given to buildings that meet standards that conserve energy, water, waste and other environmental goals.

Governments are also introducing increasingly stringent energy codes for commercial spaces. Still, more than 80% of buildings don’t have smart systems to efficiently manage their energy use.

JLL, which manages billions of square feet of commercial real estate around the world, has been making a string of investments to bring AI systems to companies looking to cut their emissions. The business case: Eco-friendly buildings charge higher rents and are on the market for less time. JLL says it expects 56% of organisations to pay a premium for sustainable spaces by 2025.

“We want to make every building out there as smart as it can be,” said Ramya Ravichandar, JLL Technologies’s vice president, technology platforms—smart and sustainable buildings. “If you can’t measure what matters, you can’t make the change.”

JLL’s investments include in Turntide, a company based in Sunnyvale, Calif. that installs electric motors coupled with small computers which learn from patterns to more precisely control heating and cooling, and Envio Systems, a Berlin-based company that develops sensors to track a building’s use, occupancy and other factors to adjust lighting, cooling and similar energy-related activities.

“Do I need to keep the lights on? Do I need to turn off the air conditioning on floor three because the entire company is working from home this week?,” Ravichandar said. “If you have a system, it is relentless and constantly processing this information.”

Generally, AI building systems learn from historical patterns and the daily habits of occupants to predict and power things on and off. For instance, software and hardware that automatically manages lights, heating and cooling can help buildings cut 20% or more of their yearly energy use.

Nevertheless, hurdles remain to installing more AI systems, including gathering data from a wide range of sources in buildings, such as sensors, which often aren’t interconnected enough. “Retrofitting existing buildings with such sensors and infrastructure, as well as ensuring consistent data quality, can be resource intensive,” Ravichandar said.

Not enough data

AI has big potential to cut the emissions of buildings, but it is only as good as the data it learns from. Only 10% to 15% of buildings have the equipment or systems in place to gather the data needed to support AI, said Thomas Kiessling, chief technology officer of Siemens Smart Infrastructure. “AI in buildings works if you have the data,” he said. “Bad data means you can’t do any kind of schedules, rules or more sophisticated use cases around artificial intelligence. You have to have the data.”

Siemens uses AI to compare one building to a thousand similar buildings to predict what the energy savings could be after an upgrade to a smart-energy management system.

“Even if you just know the address of that commercial building, and maybe you have the energy bill, and maybe you have some high level information of what kind of HVAC brand the building uses, that is these days enough to compile a profile of the building with respect to what is likely you could reap,” Kiessling said.

Otherwise, lower-cost sensors, such as for lighting and cooling, can help save energy for companies that don’t have a sophisticated management system.

Venture-capital firm Fifth Wall’s $500 million fund is focused on decarbonising buildings and invests roughly a third of its money in startups with some kind of AI offering, both in software and hardware, the fund’s co-manager Greg Smithies said. A bigger focus is using more sustainable materials, such as concrete and steel made with renewable energy.

Smithies says AI can help with quickly and cheaply identifying where it makes economic sense to upgrade buildings, fill out permits that vary between countries, draw up mock-ups of designs and come up with chemistry for sustainable materials.

“The main message overall is we’re not going to save the planet with software, and AI is software,” Smithies said. “But AI is an interesting piece of the puzzle.”