Since the COVID-19 outbreak, special attention has been paid to proper ventilation and building management systems. The indoor air CO₂ concentration level is still used as an effective indicator to evaluate indoor air quality. Many different sensors have appeared on the market in the last two years. However, calibration procedures and guidance on proper installation have not been well described by manufacturers. The research method is based on a review of technical parameters. The practical measurements of CO₂ concentration were taken using different sensors. For these purposes three different premises were selected. It was found that CO₂ measurement failure happened in residential buildings without mechanical ventilation. Meanwhile, in well ventilated buildings all sensors have shown similar results and the difference between sensors located in different zones was minimal.

As energy consumption for building engineering systems is a major part of the total energy spent, it is necessary to reduce it. This leads to the need for the development of new solutions for the control of heating, ventilation, and conditioning (HVAC) systems that are responsive to humans and their demands. In this review article, the existing research and technology advancements of the modern technologies of computer vision and neural networks for application in HVAC control systems are studied. Objectives such as human detection and location, human activity monitoring, skin temperature detection, and clothing level detection systems are important for the operation of precise, high-tech HVAC systems. This article tries to compile the latest achievements and principal solutions on how this information is acquired. Moreover, it how parameters such as indoor air quality (IAQ), variable air volume ventilation, computer vision, metabolic rate, and human clothing isolation can affect final energy consumption is studied. The research studies discussed in this review article have been tested in real application scenarios and prove the benefits of using a particular technology in ventilation systems. As a result, the modernized control systems have shown advantages over the currently applied typical non-automated systems by providing higher IAQ and reducing unnecessary energy consumption.

Enhancing energy efficiency within the building sector is imperative to curbing energy losses, given that this sector alone contributes to over 34% of global energy consumption. Employing a building management system, along with its regular updates, presents a strategic avenue to decrease energy usage, enhance building energy efficiency, and more. Tailored control strategies, aligned with the unique characteristics and usage patterns of each building, are essential for achieving energy savings. This article presents an evaluation of HVAC system efficiency in office buildings, utilizing a data-driven approach coupled with simulations conducted in IDA ICE software. The research explores the control strategy of an office building equipped with a constant air volume HVAC system, featuring a regularly controlled air handling unit. The objective is to boost energy efficiency while striking a balance between occupant comfort and energy consumption. Findings indicate that by analyzing measured data and adjusting configurable parameters, building energy consumption can be significantly reduced. Close monitoring of indoor parameters by building operators and corresponding adjustments to the HVAC system can yield energy savings of up to 16%. Leveraging these insights, the paper suggests integrating data-driven and dynamic simulation methods into building management system models to optimize HVAC systems, enhance energy efficiency, and advance ambitious carbon neutrality objectives.

Air pollution remains a major global health concern, contributing to millions of premature deaths annually. Poor indoor air quality (IAQ) is strongly associated with sick building syndrome (SBS), which can lead to various health problems and reduced workplace productivity. This study examines the role of trickle vents as a passive component in natural and hybrid ventilation systems aimed at improving IAQ and occupant comfort. Two types of factory-produced trickle vents were tested in a controlled climatic chamber under systematically varied indoor–outdoor pressure differentials, generated using a blower system. Airflow measurements revealed a strong relationship between pressure difference and vent performance. Differences between the two vent types were largely due to variations in cross-sectional areas, influencing airflow resistance and pressure drop. Although neither vent achieved the required ventilation rates for standard conditions, their integration into hybrid systems, particularly in combination with mechanical exhaust fans, was found to significantly enhance potential airflow. The findings underline both the challenges and opportunities in achieving effective ventilation, especially in upper building floors where natural driving forces are reduced. This work contributes to the understanding of passive ventilation components and their potential to support healthier, more sustainable indoor environments.