Artificial intelligence and decarbonization: The cost of a green future, brick by brick.

It is undeniable that buildings have a huge impact on the environment, with some estimating their contribution to global emissions at up to 40%, roughly equally divided between construction and operation. Furthermore, some organizations claim that nearly 90% of buildings lack software systems for energy management. However, even in the absence of systems in this area, the potential of artificial intelligence remains significant.

The construction of next-generation, sustainable, energy-efficient buildings.

The implementation of digital platforms in the operational space can lead to improvements in energy efficiency ranging from 10% to 50%, depending on the specific characteristics of the building. For example, warehouses that require lighting and have fewer heating, ventilation, and air conditioning (HVAC) systems may see lower cost savings. In the case of commercial buildings with significant fluctuations in occupancy, savings can reach up to 50%. On average, we expect a reduction in energy consumption per building of about 30%.

If we manage to increase the share of buildings equipped with energy management systems from the current 10% to over 50%, and take into account an average reduction in energy consumption of 30%, it will have a huge impact. This could potentially reduce a third of the carbon dioxide related to energy efficiency, which accounts for 20% of the global CO2 emission problem.

In recent years, there has been a clear increase in interest in energy management applications, driven by changing priorities at the corporate level, especially among Fortune 500 companies. Previously, energy management was seen as the responsibility of building managers and was not a significant issue in the overall cost structure of real estate companies. However, with rising energy prices worldwide, fueled by various geopolitical factors affecting oil and gas prices, there is an increasing awareness of the need to develop and implement decarbonization plans.

For example, countries like Germany and France are experiencing significant increases in energy prices. As a result, leaders in the real estate sector worldwide are recognizing the financial viability of investing in energy management systems. They are expecting attractive investment returns over five to seven years, with internal rates of return ranging from 20% to 30%.

To better understand the situation, when analyzing energy consumption in a commercial building, approximately one third is attributed to heating, ventilation, and air conditioning; another third goes to lighting; and the remaining portion is for other utilities, including charging stations and minor cooling needs. Focusing on optimizing HVAC and lighting systems based on occupancy patterns could be a profitable starting point, potentially followed by the integration of solar roofs and advanced storage systems to further reduce energy consumption and minimize costs.

It is important to note that these trends are particularly applicable to the American market. The dialogue with clients has significantly changed. Today, the focus is shifting from taking measures solely related to sustainability to the economic basis and promised investment returns.

If we want to build next-generation buildings that are sustainable and environmentally friendly, we need to start paying attention to how we can use artificial intelligence in design and construction. But for AI to work effectively, it requires quality data. One thing we know about the data collected by buildings is that they are traditionally gathered in various fields.

This means that we first need to understand the sources of this data. They can come from heating systems, lighting, access control, solar panels, and electric vehicle charging stations that are scattered throughout the environment and are generally not designed to interact with each other. However, with the development of the industrial Internet of Things, we see how crucial this data has become.

Now that this data is available for analysis, and with the development of data platforms specifically designed to measure the data provided by these sensors, we can start using artificial intelligence to gather information about commercial and industrial buildings, warehouses, schools, office buildings, and industrial campuses in order to gain a more comprehensive understanding of their efficiency, resource consumption, and environmental impact.

It is important to note that with the help of artificial intelligence, you can quickly gain insights about a building by comparing it to similar buildings and conditions, even with limited information.

The use of artificial intelligence for the design and construction of smart buildings

It's easy to say that designers should collaborate with construction companies, and both sides should deal with operational companies before the building design begins, the land is cleared, and the bricks are laid. In reality, these parties are like ships passing in the night and very rarely communicate with each other. Too often, we see gaps in communication between designers, operational companies, and construction, leading to inefficiencies and designs that deviate significantly from the original vision.

To gain a clearer (non-emotional) understanding, a digital twin can be used in building design. This twin provides a three-dimensional representation of the design, tenant experience, energy consumption, and carbon footprint during occupancy and full use of all systems. Now we need to add questions to the digital twin. These may include how much it costs to build a nearly zero-energy building, which materials are better, what compromises can be made when using materials, and how much the building will cost in ten years?

Although some systems may provide at least part of this information, we are still not at the stage where a comprehensive overview of the environmental impact and carbon footprint of a building can be created during the design phase. This information is necessary to determine whether to apply a full zero-impact policy or a partial approach to reducing the carbon footprint, as the results compared to the investments are negligible.

Artificial intelligence will have a significant impact on creating a comprehensive picture in the energy sector throughout the entire lifecycle and will help ensure the proper construction of buildings from the very beginning. We are currently in a phase of active research and consulting in the field of artificial intelligence. However, building managers need to have a clear understanding of what the return on investment will be when making changes.

Specifically, when using tools like ChatGPT in the decision-making process, it is indeed helpful to assist our clients in better understanding their field of activity. Although this may seem paradoxical, it will help better align the goals of artificial intelligence with business objectives and the needs of the environment. This will allow for the decarbonization of buildings based on investment feasibility rather than just environmental impact.

The future lies in transitioning from rule-based optimization to schedule-based optimization. Currently, if it's cold outside, the heating turns on, and if it's dark, the lighting turns on. This simplified approach does not take into account the many factors that can determine the need to activate or deactivate these systems. This is where artificial intelligence plays a huge role.

Conducting audits and consulting in the construction industry to understand which buildings are performing well and which are not, as well as identifying gaps, will play a crucial role in the future development of smart, energy-efficient buildings. This is where artificial intelligence will provide an advantage for those looking to build more environmentally friendly structures and decarbonize rapidly becoming costly and expensive assets.