A heating, ventilation, and air conditioning (HVAC) system provides 'conditioned air' or thermal comfort to the residents and personnel in residential and commercial buildings.

Thermal comfort is a state of mind when a person is happy and not feeling uncomfortably hot or cold. Thermal comfort varies from person to person and over time. Older HVAC systems with prefixed set points and operational schedules can cause discomfort and health issues for occupants. Workers' discomfort can affect productivity in business settings. This article will discuss the role of sensors and artificial intelligence (AI) in improving energy efficiency and indoor environmental quality by making HVACs smarter.

Need for AI-based system in HVAC control

HVAC systems constitute up to 40 per cent of overall energy consumption in buildings, whether commercial, residential, or industrial. Older systems are poorly designed, inefficient, expensive, fail to maintain comfort levels, and contribute to greenhouse gas emissions.

The uncertainty of climate control inside a building and fluctuating outdoor temperatures make it difficult for an HVAC system to function correctly. People enter and exit buildings, impacting temperature control and ventilation. Different indoor activities also affect HVAC needs. A manually controlled HVAC system cannot reach peak performance due to variable working conditions. Standard HVACs have building management systems (BMS) that run preprogrammed logic to respond to external and internal environments. Preset programs can be problematic as peak demand for HVACs occurs during the hottest hours of the day, coincidentally the most expensive energy consumption period.

Only a smart control system can process this data in real time and adjust the HVAC system. The new autonomous self-adaptive Artificial Intelligence (AI) software can develop self-operating buildings. The AI optimise airflow and other variables. Predictive controls use Machine Learning (ML) to adjust operations and analyse energy consumption patterns in anticipation of dynamic conditions. This software significantly reduces carbon emissions and delivers substantial savings.

How do AI and sensors make the HVAC system smarter?

Consumers can use the Smart AI-based HVAC systems to track and manage the building’s microclimate, reducing energy use and operating costs. They can create their ideal personal climate. Figure 1 represents a typical AI-assisted HVAC control block diagram for a building.

The core of AI-assisted building control consists of core logic and neural networks (Controller #1 in Fig. 1). Sensor feedback is the critical feature of this system control. The sensors (indoor air temperature, Relative humidity, CO2 level, PIR sensors, etc.) collect various variables (environmental and personal, among others), save them in a database, and use the system to arrive at intelligent decisions. Controller #2 shows how AI-assisted tools help the sensors for more intelligent control. optimised settings and predictive control are the most adopted functions.

Figure 1: Block diagram of the AI-assisted HVAC system

The inputs and outputs needed to generate AI-based models are interrelated to thermal comfort and energy-saving control systems. The inputs mainly relate to comfort conditions, design variables, and other indicators useful for such systems. The inputs divide into HVAC systems, indoor and outdoor climatic conditions, building geometry and components, occupant-related variables, and other groups. The outputs categorise into comfort indices, energy or load (HVAC, cooling/heating, cool/hot water), microclimate indicators (temperature, CO2 concentration), and others (including cost and time efficiency).

Benefits of using AI in HVAC

AI has promising applications in HVAC as it improves indoor air quality and energy efficiency. It can conserve superior air quality with the lowest energy consumption. Some other benefits are:

Additional control: You can quickly reprogram your smart HVAC system if you retrofit your existing building for a new purpose.

Small investments: You do not need to change the existing hardware or software parts for new ones to make a system upgrade.

Future of HVAC systems with AI

The purpose of creating an HVAC simulation and implementation of AI is to reduce energy costs, peak demand, and consumption. AI is rapidly making inroads into the construction industry. It brings energy efficiency methods focusing on HVAC since the HVAC systems consume the most energy in residential and commercial buildings. AI improves energy efficiency and indoor air quality by managing ventilation, temperature, and humidity with minimum energy consumption.


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