Thermal comfort modeling in transient conditions using real-time local body temperature extraction with a thermographic camera

2018 ◽  
Vol 143 ◽  
pp. 36-47 ◽  
Author(s):  
Andrei Claudiu Cosma ◽  
Rahul Simha
2020 ◽  
Vol 11 (4) ◽  
Author(s):  
João Marcos de Carvalho Vasconcelos ◽  
Sindynara Ferreira ◽  
Elisa De Souza Junqueira Rezende ◽  
José Luiz de Andrade Rezende Pereira

This study was conducted to investigate the thermoregulation of Holstein cattle in an adapted free-stall facility at IFSULDEMINAS, Campus Inconfidentes, by measuring thermal comfort indices. The experimental period was from the end of December 2012 to the start of January 2013, in a total of 16 days. 12 multiparous, lactating, black-and-white Holstein cows were used in a free-stall system. Rectal temperature, respiratory frequency, ambient temperature and relative humidity were recorded at 3:00 a.m., 7:00 a.m., 11:00 a.m., 3:00 p.m., 7:00 p.m. and 11:00 p.m. The results demonstrate that despite the temporal variations that occurred throughout the evaluation days, the confined animals maintained their body temperature in balance.


2021 ◽  
Vol 246 ◽  
pp. 03005
Author(s):  
Eusébio Conceição ◽  
João Gomes ◽  
Mª Manuela Lúcio ◽  
Hazim Awbi

In this numerical study the energy production in solar collectors in a University building used to improve the internal thermal conditions is made. Passive and active solutions, using external solar collector and internal thermo-convectors, are used. The numerical simulation, in transient conditions, is done for a winter typical day with clean sky. This numerical study was carried out using a software that simulates the Building Dynamic Response with complex topology in transient conditions. The software evaluates the human thermal comfort and indoor air quality levels that the occupants are subjected, Heated Ventilation and Air Conditioned energy consumption, indoor thermal variables and other parameters. The university building has 107 compartments and is located in a Mediterranean-type environment. External solar water collectors, placed above the building’s roof, and internal thermo-convectors of water/air type, using mixing ventilation, are used as passive and active strategies, respectively. The thermal comfort level, using the Predicted Mean Vote index, and the indoor air quality, using the carbon dioxide concentration, are evaluated. The results show that in winter conditions the solar collectors improve the thermal comfort conditions of the occupants. The indoor air quality, in all ventilated spaces, is also guaranteed.


2021 ◽  
Vol 9 ◽  
Author(s):  
Sharnil Pandya ◽  
Anirban Sur ◽  
Nitin Solke

The presented deep learning and sensor-fusion based assistive technology (Smart Facemask and Thermal scanning kiosk) will protect the individual using auto face-mask detection and auto thermal scanning to detect the current body temperature. Furthermore, the presented system also facilitates a variety of notifications, such as an alarm, if an individual is not wearing a mask and detects thermal temperature beyond the standard body temperature threshold, such as 98.6°F (37°C). Design/methodology/approach—The presented deep Learning and sensor-fusion-based approach can also detect an individual in with or without mask situations and provide appropriate notification to the security personnel by raising the alarm. Moreover, the smart tunnel is also equipped with a thermal sensing unit embedded with a camera, which can detect the real-time body temperature of an individual concerning the prescribed body temperature limits as prescribed by WHO reports. Findings—The investigation results validate the performance evaluation of the presented smart face-mask and thermal scanning mechanism. The presented system can also detect an outsider entering the building with or without mask condition and be aware of the security control room by raising appropriate alarms. Furthermore, the presented smart epidemic tunnel is embedded with an intelligent algorithm that can perform real-time thermal scanning of an individual and store essential information in a cloud platform, such as Google firebase. Thus, the proposed system favors society by saving time and helps in lowering the spread of coronavirus.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zeynep Birgonul

PurposeThe heating, ventilation and air conditioning systems are responsible for a significant proportion of the energy consumption of the built environment, on which the occupant's pursuit of thermal comfort has a substantial impact. Regarding this concern, current software can assess and visualize the conditions. However; integration of existing technologies and real-time information could enhance the potential of the solution proposals. Therefore, the purpose of this research is to explore new possibilities of how to upgrade building information modeling (BIM) technology to be interactive; by using existing BIM data during the occupation phase. Moreover, the research discusses the potential of enhancing energy efficiency and comfort maximization together by using the existing BIM database and real-time information concomitantly.Design/methodology/approachThe platform is developed by designing and testing via prototyping method thanks to Internet of things technologies. The algorithm of the prototype uses real-time indoor thermal information and real-time weather information together with user's body temperature. Moreover, the platform processes the thermal values with specific material information from the existing BIM file. The final prototype is tested by a case study model.FindingsThe outcome of the study, “Symbiotic Data Platform” is an occupant-operated tool, that has a hardware, software and unique Revit-Dynamo definition that implies to all BIM files.Originality/valueThe paper explains the development of “Symbiotic Data Platform”, which presents an interactive phase for BIM, as creating a possibility to use the existing BIM database and real-time values during the occupation phase, which is operated by the occupants of the building; without requiring any prior knowledge upon any of the BIM software or IoT technology.


2020 ◽  
Vol 174 ◽  
pp. 105453
Author(s):  
Hanwook Chung ◽  
Jingjie Li ◽  
Younghyun Kim ◽  
Jennifer M.C. Van Os ◽  
Sabrina H. Brounts ◽  
...  

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