AI in HVAC

AI in HVAC (Artificial Intelligence in Heating, Ventilation, and Air Conditioning)

Technology

HVAC equipment operates under the control of automation systems or a building management system. These automation systems have a fixed operation and can only react to the external & internal environment according to programmed logic. Times of peak demand are often the most expensive times to use energy and occur during the hottest hours of the day when HVAC is needed the most. New fully autonomous self-adaptive Artificial Intelligence (AI) software is designed to deliver significant savings and dramatically reduce carbon emissions, enabling a self-operating building.

In work with artificial intelligence applications, optimizing variables such as airflow is best. Peak demand times are often the most expensive times to use energy and occur during the hottest hours of the day when the HVAC system is most needed. Air quality for humidity and temperature with much lower energy consumption is also achievable. The goal of creating HVAC simulations and eventually applying AI is to reduce the amount of energy used and save time by automating frustrating and repetitive tasks.

Heating, Ventilation, and Air Conditioning (HVAC) systems account for substantial energy consumption, up to 40% of total energy consumption in buildings, regardless of the type of building – commercial, residential, or industrial. HVAC equipment operates under the control of automation systems or a building management system (BMS). They are in place to safeguard the production of heat/cold and ensure it is distributed appropriately in order to keep the temperature in the desired range. These automation systems have a fixed operation and can only react to the external & internal environment according to programmed logic.

Real estate and AI in HVAC

The work of AI in HVAC in real estate starts with the creation of a digital twin of a building that helps AI explore a building, detect patterns, simulate building usage, and predict future requirements. This huge amount of data needed to be processed requires more processing power that only artificial intelligence can handle. The trained algorithm is then connected to the current BMS to control existing HVAC technologies. Once deployed, HVAC control is automatically managed by AI, reducing energy costs and carbon footprint.

Innovative AI algorithms deliver results by simplifying management by auto-tuning HVAC systems. By taking into account all parameters (climate, zonal use, comfort index factors, etc.), AI delivers HVAC efficiency that maximizes occupant comfort and minimizes energy consumption.

Net-Zero and AI in HVAC

Carbon dioxide emissions from buildings reached an all-time high in 2019 and were responsible for 28 percent of global emissions, according to an International Energy Agency report. Heating, ventilation and air conditioning systems account for more than 50 percent of this. Buildings are one of the biggest contributors to carbon emissions – in fact, they produce almost a fifth of the world’s carbon emissions and consume around 40% of the world’s primary energy. Also, 30% of energy used in commercial real estate is wasted. The use of AI in HVAC technology in buildings will be able to reduce emissions by up to 90%. AI technology offers a tremendous opportunity for HVAC optimization for cost- and time-effectiveness. AI algorithms deliver superior results simplifying the management through automatic adjustments of HVAC systems. The use of AI in HVAC will help humanity achieve net-zero.

AI in HVAC can help to adapt to the impacts of climate change by improving people's ability to predict extreme weather events and providing decision-support tools to help people to respond more effectively.

The Role of Deep Reinforcement Learning

Deep Reinforcement Learning (DRL) is a more efficient method of mathematical modeling. The sophisticated game-theory-approach of DRL builds on pattern finding and introduces an incentive-based system to reward constant improvement and finding better results. This additional complexity results in unparalleled accuracy and a significant reduction in algorithm training time, delivering better end results.

The application of DRL in AI in HVAC technology shows the following results:

Up to 30% reduction in total energy and coolant/heating cost
30-40% decrease in carbon footprint
60% improvement in building occupant comfort

Hospitals and AI in HVAC

Hospitals are evolving, resulting in a wide variety of campuses with complex wings and buildings with very different ages and uses that waste a huge amount of energy. Technology multi-cloud AI works across any BMS system and HVAC infrastructure within hospitals – optimizing energy, safety and comfort from the most advanced to the longest-standing facilities. Aseptic operating theatres, recovery wards, consultation rooms, kitchens and so much more mean hospitals have the most diverse temperature, humidity, air quality and airflow needs technology can work with. The artificial intelligence underlying technology allows the hospital to be divided into zones, sections of each building, to optimize energy and comfort for each unique microclimate.

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External links

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