Emerging Technologies

This AI helps buildings cool themselves and cut emissions

Automated AI-enabled systems can help buildings optimize heating and cooling for greater efficiency and sustainability.

Automated AI-enabled systems can help buildings optimize heating and cooling for greater efficiency and sustainability. Image: Unsplash/Nerses97

Johnny Wood
Writer, Forum Agenda
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  • Automated AI-enabled systems can help buildings optimize heating and cooling for greater efficiency and sustainability.
  • This will help us tackle the emissions generated by our built environment, says Sam Ramadori, President of BrainBox AI, a company that develops automated AI solutions for buildings.
  • But AI systems need guardrails and a multi-sector approach to ensuring they keep tech safe and inclusive - a challenge addressed in the World Economic Forum’s Privacy and Safety in the Metaverse report.

Smart buildings are fueled by data. In tomorrow’s homes and offices, sensors will harvest ever-greater volumes of information to feed cloud-based, AI-enabled systems that can boost building efficiency, while reducing costs and emissions.

The benefits of AI-enabled buildings don’t stop there. Algorithms can also make residences and workplaces more comfortable, which bolster occupants’ health and well-being.

Sam Ramadori, President of BrainBox AI, is part of a team developing automated artificial intelligence solutions that train buildings to make smart decisions about temperature, energy use, efficiency and cost savings. He talked to the World Economic Forum about the high-tech buildings of the future – and the present.

Data is reshaping tomorrow’s buildings

“We came together to tackle the emissions generated by our built environment. It's stated that the buildings that we work, live and play in account for over 38% of GHG emissions globally. Part of that comes from the construction of new buildings, but the majority of it comes from the daily operations of those buildings. They are by far the biggest energy consumers on our planet,” Ramadori said.

The goal is to use cloud technology to combine a building’s sensor-generated internal data with external sources of data – such as weather conditions, energy costs and if energy supply is generated using fossil fuels or cleaner sources – that impact a building’s energy use. The system can decide the optimal time to reduce or increase heating or cooling levels, taking into account factors like grid demand, energy tariffs and building occupancy levels, for example.

“All that richness of data can be brought together and then leveraged using the new capabilities that we have at our fingertips through artificial intelligence, which can both learn that building in a super granular fashion room by room, but then also make autonomous decisions that are much smarter using that data than a simple thermostat on the wall,” Ramadori said.

The technology is already at work, with AI-enabled cloud-based solutions being installed across parts of North America, including Canada's largest mattress store, which has more than 200 locations spread across the country.

“The advent of the cloud allows us to deploy those stores in a way that's really efficient and economical. And they've seen very material energy consumption savings of over 20%, both on electricity and gas.”

“If you step back and you look at those buildings, we like to say that we've in essence woken them up,” said Ramadori. “Where it gets really exciting - in terms of smart cities, sustainable cities - is where you have hundreds or thousands of buildings in this state of being awake.”

Building the future

Algorithms and digital solutions are transforming buildings in other ways, too.

Optimizing energy use extends to solar panel installation, smart airflow designs and even harvesting power from people exercising at an on-site gym.

Advanced AI-systems can also close down entire sections of a building that aren’t being used, to cut energy costs. While a standard occupancy sensor registers light, shade and temperature changes when someone enters a room, intelligent systems can determine if a small number of people have triggered multiple sensors and reduce energy in areas that are not essential, for example.

Visitors to some AI-enabled buildings could be welcomed by a smart concierge, which helps them find their way around, book appointments and even arrange a taxi.

Smart systems can also help optimize building security by deploying solutions like facial recognition systems, and employee safety through contactless interactions, which help reduce direct contact during a pandemic.

Buildings can use predictive maintenance to identify problems before they occur and to schedule maintenance, repairs and necessary downtime to avoid inconvenience and reduce long-term costs.

Sophisticated systems can create a digital twin or digital replica of a building, which can be used to optimize how a building operates, improve energy and other efficiencies and reduce emissions.


How is the World Economic Forum ensuring the responsible use of technology?

Guardrails for AI

A number of AI-enabled buildings have developed smartphone apps, where users can log-in to schedule meetings, book a desk space, assign or get directed to a parking space or locate colleagues. Apps can also help with navigation and give updates on traffic conditions.

State-of-the-art cloud-based AI systems in buildings can integrate with an app to assign employees to a workstation and communicate their personal preferences to IoT sensors, which preset the temperature, humidity and lighting to create the ideal working environment.

 Graphs illustrating the test scores of the AI relative to human performance.
AI language and image recognition systems have rapidly evolved in the past decade. Image: Our World in Data

AI capabilities have accelerated over the past decade, especially in the fields of language and image recognition. In the early days, systems could not provide language or image recognition at a human level. Now, AI systems can outperform humans in these areas, although there are inconsistencies in some AI output.

There have also been concerns expressed about the potential harm runaway AI development could cause, with a number of AI experts and tech leaders calling for a pause in unregulated AI development.

The World Economic Forum’s Privacy and Safety in the Metaverse report contains recommendations for developing a safe and inclusive metaverse, for example. However, the fast pace of AI development makes regulating the metaverse, AI large language models and some other transformative artificial intelligence developments a major challenge.

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