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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Article From Facial Expressions to Thermal Sensation: POMS-Validated AI-Based Mood Estimation Driving Psychology-Adaptive HVAC Control(Elsevier Science SA, 2026-06) Saleh Saleh, Yousif Abed; Sümer, Mustafa Erdi; Saleh, Yousif Abed Saleh; Lotfi, Bahram; Turhan, Cihan; Özbey, Mehmet FurkanThe psychological state of building occupants plays a critical role in how thermal environments are perceived and experienced, yet conventional Heating, Ventilation, and Air Conditioning (HVAC) control strategies largely ignore this factor. Current systems typically focus on environmental and personal parameters, overlooking the influence of mood state on thermal comfort. This omission can lead to suboptimal comfort levels, decreased occupant satisfaction, and inefficient energy use. Integrating psychological feedback into the HVAC control has the potential to transform indoor climate management into a truly occupant-centric process. To this aim, this study presents a novel framework that employs artificial intelligence (AI) and image processing together to estimate occupants' mood states in real time. Facial expressions are analysed using a deep learning-based computer vision model, and the resulting mood predictions are validated with the Profile of Mood States (POMS) questionnaire to ensure accuracy and reliability. Validated mood data directly informs the HVAC setpoint adjustments, enabling psychology-adaptive control that responds dynamically to occupants' current mood states. Moreover, the system operates in real time, combining low-latency image analysis with adaptive control algorithms to continuously align thermal conditions with validated mood estimations. Additionally, implementing mood-driven HVAC control shows potential for enhancing perceived comfort while improving energy efficiency. By bridging the gap between psychological state assessment and environmental control, this research contributes to the advancement of intelligent building systems, paving the way for more responsive, energy-conscious, and human-centered indoor environments.Article Simulation-Based Optimization of HVAC Systems in Aging Educational Facilities: Addressing IAQ Challenges Through Retrofitting(MDPI, 2026-03-20) Saleh, Yousif Abed Saleh; Turhan, Cihan; Turhan, BurcuIndoor air quality (IAQ) in educational buildings plays a critical role in the health, cognitive performance, and well-being of occupants. Aging university facilities often rely on outdated ventilation systems that are not designed to meet current demands or respond to dynamic occupancy levels. This study investigates the performance and feasibility of various advanced ventilation strategies in comparison to an existing balanced mechanical ventilation (BMV) system in a university classroom accommodating 100 students. Using a Dynamic Building Energy Simulation Program, simulations were conducted to evaluate IAQ (using CO2 levels), energy consumption, and thermal comfort under three retrofitting scenarios: BMV, demand-controlled ventilation (DCV), and hybrid ventilation combining natural and mechanical airflow. The simulations indicate that DCV cuts annual HVAC energy use by 33% relative to the baseline, while the hybrid strategy achieves the greatest reduction of 42% and maintains CO2 levels and thermal comfort within recommended limits. Although hybrid systems provide seasonal advantages, their complexity may limit applicability. In addition to technical analysis, this study also explores the financial and tax-related challenges associated with retrofitting ventilation systems in university buildings. Investment payback periods, operational costs, and potential tax incentives are discussed to evaluate economic viability. Overall, the endorse hybrid ventilation as the most cost-effective strategy where mixed-mode control is feasible, and DCV as a practical alternative for buildings unable to employ natural ventilation.Article Citation - WoS: 4Citation - Scopus: 5Latent Psychological Pathways in Thermal Comfort Perception: The Mediating Role of Cognitive Uncertainty on Depression and Vigour(MDPI, 2025-07-18) Ozbey, Mehmet Furkan; Turhan, Cihan; Alkan, Nese; Akkurt, Gulden GokcenThermal comfort is the condition of mind that expresses satisfaction with the thermal environment, and it is assessed through subjective evaluation, according to the American Society of Heating, Refrigerating, and Air-Conditioning Engineers. While research has traditionally emphasised physical factors, growing evidence highlights the role of the state of mind in shaping thermal perception. In a prior Monte Carlo sensitivity analysis, six mood subscales-Anger, Confusion, Vigour, Tension, Depression, and Fatigue-were examined for how they affect the absolute difference between actual and predicted thermal sensation. Depression and vigour were found to be the most influential, while confusion appeared least impactful. However, to accurately assess the role of confusion, it is necessary to consider its potential interactions with other mood subscales. To this end, a mediation analysis was conducted using Hayes' PROCESS tool. The mediation analyses revealed that confusion partially mediated depression's effect in males and vigour's effect in females. These results suggest that, despite a weak direct impact, confusion critically influences thermal perception by altering the effects of key mood states. Accounting for the indirect effects of mood states may lead to more accurate predictions of human sensory experiences and improve the design of occupant-centred environments.Article Citation - WoS: 4Citation - Scopus: 4Integrating Personalized Thermal Comfort Devices for Energy-Efficient and Occupant-Centric Buildings(Mdpi, 2025-04-26) Turhan, Cihan; Carpino, CristinaPersonalized thermal comfort (PTC) systems aim to satisfy the individual thermal preferences of occupants rather than relying on average comfort indices. With the growing emphasis on sustainability and reducing energy consumption in buildings, energy efficiency has become a critical factor in the design and selection of PTC systems. While the development of PTC tools has accelerated in the last decade, selecting the most appropriate system remains a challenge due to the dynamic, uncertain, and multi-dimensional nature of the decision-making process. This study introduces a novel application of the KEMIRA-M multi-criteria decision-making (MCDM) method to identify the optimal PTC system for university office buildings-an area with limited prior investigation. A case study is conducted in a naturally ventilated office space located in a temperate climate zone. Eight distinct PTC alternatives are evaluated, including data-driven HVAC systems, wearable devices, and localized conditioning units. Six key criteria are considered: estimated energy consumption, capital cost, indoor and outdoor space requirements, system complexity, mobility, and energy efficiency. The results indicate that wearable wristbands, which condition the occupant's carpus area, offer the most balanced performance across criteria, while radiant ceiling/floor systems perform the poorest. Energy efficiency plays a crucial role in this evaluation, as it directly impacts both the operational cost and the environmental footprint of the system. The study's findings provide a structured and adaptable framework for HVAC engineers and designers to integrate PTC systems into occupant-centric and energy-efficient building designs.Article Citation - WoS: 10Citation - Scopus: 10Modeling the Mood State on Thermal Sensation With a Data Mining Algorithm and Testing the Accuracy of Mood State Correction Factor(Pergamon-elsevier Science Ltd, 2025-01) Yerlikaya-Ozkurt, Fatma; Ozbey, Mehmet Furkan; Turhan, CihanPsychology is proven as an influencing factor on thermal sensation. On the other hand, mood state is one of the significant parameters in psychology field. To this aim, in the literature, mood state correction factor on thermal sensation (Turhan and Ozbey coefficients) is derived utilizing with data-driven black-box model. However, novel models which present analytical form of the mood state correction factor should be derived based on the several descriptive variables on thermal sensation. Moreover, the result of this factor should also be checked with analytical model results. Therefore, this study investigates the modelling of mood state correction factor with a data mining algorithm, called Multivariate Adaptive Regression Splines (MARS). Additionally, the mood state is also taken as a thermal sensation parameter besides environmental parameters in this algorithm. The same data, which are collected from a university study hall in a temperate climate zone, are used and the model results are compared with the thermal sensation results based on mood state correction factor which is driven via black-box model. The results show that coefficient of correlation "r" between the MARS and black-box model is found as 0.9426 and 0.9420 for training and testing. Hence, the mood state is also modelled via a data mining algorithm with a high accuracy, besides the black-box model.Article Citation - WoS: 6Citation - Scopus: 5Reconstructing Energy-Efficient Buildings After a Major Earthquake in Hatay, Türkiye(Mdpi, 2024-07-04) Saleh, Yousif Abed Saleh; Akkurt, Gulden Gokcen; Turhan, Cihan; Gokcen Akkurt, GuldenT & uuml;rkiye's earthquake zone, primarily located along the North Anatolian Fault, is one of the world's most seismically active regions, frequently experiencing devastating earthquakes, such as the one in Hatay in 2023. Therefore, reconstructing energy-efficient buildings after major earthquakes enhances disaster resilience and promotes energy efficiency through retrofitting, renovation, or demolition and reconstruction. To this end, this study proposes implementing energy-efficient design solutions in dwelling units to minimize energy consumption in new buildings in Hatay, Southern Turkiye, an area affected by the 2023 earthquake. This research focused on a five-story residential building in the district of Kurtlusar & imath;maz & imath;, incorporating small-scale Vertical-Axis Wind Turbines (VAWTs) with thin-film photovoltaic (PV) panels, along with the application of a green wall surrounding the building. ANSYS Fluent v.R2 Software was used for a numerical investigation of the small-scale IceWind turbine, and DesignBuilder Software v.6.1.0.006 was employed to simulate the baseline model and three energy-efficient design strategies. The results demonstrated that small-scale VAWTs, PV panels, and the application of a green wall reduced overall energy use by 8.5%, 18%, and 4.1%, respectively. When all strategies were combined, total energy consumption was reduced by up to 28.5%. The results of this study could guide designers in constructing innovative energy-efficient buildings following extensive demolition such as during the 2023 earthquake in Hatay, T & uuml;rkiye.Article Citation - WoS: 26Citation - Scopus: 30The Influence of Meteorological Parameters on Pm<sub>10</Sub>: a Statistical Analysis of an Urban and Rural Environment in Izmir/Turkiye(Mdpi, 2023-02-21) Birim, Necmiye Gulin; Turhan, Cihan; Atalay, Ali Serdar; Gokcen Akkurt, GuldenAir pollution is a substantial menace, especially in industrialized urban zones, which affects the balance of the environment, life of vital organisms and human health. Besides the main causes of air pollution such as dense urbanization, poor quality fuels and vehicle emissions, physical environment characteristics play an important role on air quality. Therefore, it is vital to understand the relationship between the characteristics of the natural environment and air quality. This study examines the correlations between the PM10 pollutant data and meteorological parameters such as temperature (T-air), relative humidity (RH), and wind speed (WS) and direction (WD) under the European Union's Horizon 2020 project. Two different zones (Vilayetler Evi as an urban zone and Sasali Natural Life Park as a rural zone) of Izmir Province in Turkiye are used as a case study and the PM10 data is evaluated between 1 January 2017 and 31 December 2021. A one-tailed t-test is used in order to statistically determine the relationships between the PM10 pollutant data and meteorological parameters. As a further study, practical significance of the parameters is investigated via the effect size method and the results show that the RH is found to be the most influencing parameter on the PM10 for both zones, while T-air is found to be statistically non-significant.Article Citation - WoS: 19Citation - Scopus: 21Gender Inequity in Thermal Sensation Based on Emotional Intensity for Participants in a Warm Mediterranean Climate Zone(Elsevier France-editions Scientifiques Medicales Elsevier, 2023-03) Ceter, Aydin Ege; Ozbey, Mehmet Furkan; Turhan, CihanThe deficiencies of the one of the most preferred conventional thermal comfort models, the Predicted Mean Vote/ Percentage of Predicted Dissatisfied (PMV/PPD) method have emerged over time since the model does not take psychological parameters such as personal traits, mood states and adaptation into account. Therefore, re-searchers have focused on Adaptive Thermal Comfort models that integrate human behaviours into the model for better prediction of thermal comfort. In addition to the influence of the behaviours of occupants, thermal comfort may be evaluated as a subjective term, thus, the effect of one of the psychological parameters, current mood state, on thermal sensation cannot be ignored for predictions. Although, the effect of current mood state on thermal sensation is a vital concept, the findings of the studies are not effective and comprehensive in the literature. For this reason, the aim of this study is to examine the relationship between current mood state and thermal sensation in gender difference aspect. Therefore, a series of experiments were conducted in a university study hall between August 16th, 2021 and August 1st, 2022. The current mood states of the participants were evaluated with the Profile of Mood States (POMS) questionnaire and the results were represented by a novel approach called Emotional Intensity Score (EIS). One tailed t-test was applied for investigating the relationship between the EIS and the thermal sensation. Findings of the research showed that a significant association exists between the EIS and thermal sensation for male participants while no relationship was found for female.Article Citation - WoS: 34Citation - Scopus: 35A Novel Data-Driven Model for the Effect of Mood State on Thermal Sensation(Mdpi, 2023-06-29) Turhan, Cihan; Ozbey, Mehmet Furkan; Ceter, Aydin Ege; Akkurt, Gulden GokcenThermal comfort has an important role in human life, considering that people spend most of their lives in indoor environments. However, the necessity of ensuring the thermal comfort of these people presents an important problem, calculating the thermal comfort accurately. The assessment of thermal comfort has always been problematic, from past to present, and the studies conducted in this field have indicated that there is a gap between thermal comfort and thermal sensation. Although recent studies have shown an effort to take human psychology into account more extensively, these studies just focused on the physiological responses of the human body under psychological disturbances. On the other hand, the mood state of people is one of the most significant parameters of human psychology. Thus, this paper investigated the effect of occupants' mood states on thermal sensation; furthermore, it introduced a novel "Mood State Correction Factor" (MSCF) to the existing thermal comfort model. To this aim, experiments were conducted at a mixed-mode building in a university between 15 August 2021 and 15 August 2022. Actual Mean Vote (AMV) and Profile of Mood States (POMS) were used to examine the effect of mood state on thermal sensation. The outcomes of this study showed that in the mood states of very pessimistic and very optimistic, the occupants felt warmer than the calculated one and the MSCFs are calculated as -0.125 and -0.114 for the very pessimistic and very optimistic mood states, respectively. It is worth our time to note that the experiments in this study were conducted during the COVID-19 Global Pandemic and the results of this study could differ in different cultural backgrounds.Article Citation - WoS: 18Citation - Scopus: 21An Integrated Decision-Making Framework for Mitigating the Impact of Urban Heat Islands on Energy Consumption and Thermal Comfort of Residential Buildings(Mdpi, 2023-06-16) Turhan, Cihan; Atalay, Ali Serdar; Akkurt, Gulden Gokcen; Gokcen Akkurt, GuldenUrban heat island (UHI) is a zone that is significantly warmer than its surrounding rural zones as a result of human activities and rapid and dense urbanization. Excessive air temperature due to the UHI phenomenon affects the energy performance of buildings and human health and contributes to global warming. Knowing that most of the building energy is consumed by residential buildings, therefore, developing a framework to mitigate the impact of the UHI on residential building energy performance is vital. This study develops an integrated framework that combines hybrid micro-climate and building energy performance simulations and multi-criteria decision-making techniques. As a case study, an urban area is analyzed under the Urban GreenUP project funded by the European Union's Horizon 2020 Programme. Four different strategies to mitigate the UHI effect, including the current situation, changing the low-albedo materials with high-albedo ones, nature-based solutions, and changing building facade materials, are investigated with a micro-climatic simulation tool. Then, the output of the strategies, which is potential air temperature, is used in a dynamic building energy simulation software to obtain energy consumption and thermal comfort data of the residential buildings in the case area. Finally, a multi-criteria decision-making model, using real-life criteria, such as total energy consumption, thermal comfort, capital cost, lifetime and installation flexibility, is used to make a decision for decreasing the UHI effect on residential energy performance of buildings. The results showed that applying NBSs, such as green roofs and changing existing trees with high leaf area density ones, have the highest ranking among all mitigation strategies. The output of this study may help urban planners, architects, and engineers in the decision-making processes during the design phase of urban planning.