Browsing by Author "Ahsan M"

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Accurate Facial Temperature Measurement Using Low-Cost Thermal Camera for Indoor Thermal Comfort Applications
(MDPI AG, Basel, 2025-11) Ahsan M; Shahzad W; Arif KM
Non-contact measurement of human skin temperature is an important area of research. Infrared temperature devices have played a critical role in measuring skin temperature without physical contact. Thermal cameras have also been employed for non-contact skin temperature measurements. However, both infrared devices and thermal cameras have limitations that restrict their use in the building industry for assessing occupant thermal comfort. The building industry requires sophisticated equipment capable of measuring human temperature non-invasively and, through integration with building control systems, adjusting the environment to meet occupants’ thermal comfort needs. Unfortunately, standard thermal cameras and infrared temperature sensors are not designed with building applications in mind. This paper proposes an affordable and building-compatible thermal camera designed to measure occupant skin temperature via a non-contact method, enabling better integration with building control systems to support occupant comfort. Experimental results demonstrate that the proposed system can reliably capture facial skin temperature and establish a quantifiable relationship between facial and room temperatures. Moreover, this provides a foundation for future real-time thermal comfort and building-control applications.
AI-Based Controls for Thermal Comfort in Adaptable Buildings: A Review
(MDPI AG, 2024-11-04) Ahsan M; Shahzad W; Arif K
Due to global weather changes and pandemics, people are more likely to spend most of their time in indoor environments. In this regard, indoor environment quality is a very important aspect of occupant well-being, which is often ignored in modern building designs. Based on our research, thermal comfort is one of the essential items in building environments that can improve the mental stability and productivity of the occupants if the building’s indoor environment is created in a way that meets the occupants’ comfort requirements. Buildings nowadays operate on adaptive or stationary models to attain thermal comfort, which is based on Fanger’s model of the Predicted Mean Vote (PMV). Based on the literature review, limited work has been carried out to enhance the quality of the inside environment, and most research work has been devoted to building energy management. Moreover, there have been no definite solutions so far that have the capability to detect the thermal comfort requirements of multiple occupants in real time. Modern buildings tend to operate on predefined set point parameters to control the indoor environment based on the measured room temperature, which can be different from the thermal comfort requirements of the occupants. This paper discusses the limitations and assumptions that are associated with the existing thermal comfort solutions and emphasises the importance of having a real-time solution to address the thermal requirements of occupants.