Thermal comfort is crucial to well-being and work productivity. Human thermal comfort is mainly controlled by HVAC (heating, ventilation, air conditioning) systems in buildings. However, the control metrics and measurements of thermal comfort in HVAC systems are often oversimplified using limited parameters and fail to accurately control thermal comfort in indoor climates. Traditional comfort models also lack the ability to adapt to individual demands and sensations. This research developed a data-driven thermal comfort model to improve the overall thermal comfort of occupants in office buildings. An architecture based on cyber-physical system (CPS) is used to achieve these goals. A building simulation model is built to simulate multiple occupants' behaviors in an open-space office building. Results suggest that a hybrid model can accurately predict occupants' thermal comfort level with reasonable computing time. In addition, this model can improve occupants' thermal comfort by 43.41% to 69.93%, while energy consumption remains the same or is slightly reduced (1.01% to 3.63%). This strategy can potentially be implemented in real-world building automation systems with appropriate sensor placement in modern buildings.
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http://dx.doi.org/10.3390/s23104857 | DOI Listing |
Air conditioning systems are widely used to provide thermal comfort in hot and humid regions, but they also consume a large amount of energy. Therefore, accurate and reliable load demand forecasting is essential for energy management and optimization in air conditioning systems. Within the current paper, a novel model on the basis of machine learning has been presented for dynamic optimal load demand forecasting in air conditioning systems.
View Article and Find Full Text PDFNurs Rep
December 2024
Comprehensive Health Research Centre (CHRC), University of Evora, 7000-811 Evora, Portugal.
Background/objectives: The health of migrant populations is strongly influenced by social, cultural, and environmental factors. Promoting health literacy (HL) is essential to empower these populations and reduce health inequalities. We aimed to assess the perceptions and behaviors of migrants residing in a neighborhood within a municipality in the Metropolitan Area of Lisbon regarding health risks arising from environmental conditions, as well as to determine their level of health literacy.
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January 2025
Research Group in Bioclimatology, Ethology and Animal Welfare (BioEt), Department of Animal Science, Federal University of Paraiba, Areia, Paraiba, Brazil.
Japanese quails () are sensitive to zinc (Zn) deficiency, a mineral essential for growth, development, and bone health. This study evaluated the effects of different levels of Zn in the diet on zootechnical performance, organ and carcass weight, and tibial breakage resistance in quails from 1 to 42 days of age. A 5 × 2 factorial design was used, consisting of five Zn levels (30, 60, 90, 120, and 150 mg/kg) and two thermal environments (thermal comfort and heat stress), with five replicates of 10 birds per treatment.
View Article and Find Full Text PDFRev Environ Health
January 2025
School of Architecture and Design, Harbin Institute of Technology, Harbin, China.
The school built environment is closely related to children's health, and research on this topic is increasing. However, bibliometric analyses seeking to provide a comprehensive understanding of the research landscape and key themes in the field are lacking. This study comprehensively explored the global trends and research hotspots on the associations between school built environment and children's health.
View Article and Find Full Text PDFJ Therm Biol
January 2025
School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Private Bag X3, Wits, 2050, South Africa. Electronic address:
Questionnaires exploring tourists' perceptions of ideal climatic conditions are argued to be a more suitable data source for the development of tourism climate indices than the utilization and integration of expert opinion and pre-established thresholds. This assumes that those tourist respondents can accurately quantify meteorological conditions at a given point in time, and effectively discriminate between meteorological thresholds of suitable and unsuitable conditions. For variables such as rainfall and sunshine hours, this assumption is fairly reasonable.
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