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  4. A BIM-based approach towards personalized low-cost thermal comfort monitoring using digital twins
 
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A BIM-based approach towards personalized low-cost thermal comfort monitoring using digital twins

Publikationstyp
Conference Paper
Date Issued
2024-07
Sprache
English
Author(s)
Chillón Geck, Carlos  
Digitales und autonomes Bauen B-1  
Alsaad, Hayder  
Völker, Conrad  
Smarsly, Kay  
Digitales und autonomes Bauen B-1  
TORE-URI
https://hdl.handle.net/11420/50362
Start Page
355
End Page
364
Citation
31st International Workshop on Intelligent Computing in Engineering, EG-ICE 2024
Contribution to Conference
31st International Workshop on Intelligent Computing in Engineering, EG-ICE 2024  
Scopus ID
2-s2.0-85207165176
Heating, ventilation, and air conditioning (HVAC) systems help regulate indoor temperatures to maintain the comfort and productivity of building occupants. However, the global climate and energy crisis requires robust energy conservation measures to reduce electricity and heat consumption, particularly in HVAC-dominated building operations. To reduce energy consumption caused by building operations, the digital twin (DT) concept has focused on integrating new technologies and methodologies, such as the Internet of Things and building information modelling (BIM), for application in the field of thermal comfort and energy management. However, the adoption of digital twins faces limitations, including insufficient research on personalized thermal comfort models and a lack of consensus in the definition and design of digital twins. This study addresses the limitations by using a formal foundation to implement a BIM-based DT for personalized thermal comfort monitoring that integrates indoor environmental data and occupant feedback for analysis, visualization, and control of personalized thermal comfort in buildings.
Subjects
digital twins
indoor environment
Internet of Things (IoT)
Personalized thermal comfort
smart monitoring
DDC Class
005: Computer Programming, Programs, Data and Security
690: Building, Construction
Funding(s)
Verbundprojekt: Automatische Bewertung von Monitoringdaten von Infrastrukturbauwerken mithilfe von KI und IoT - IDA-KI -, Teilvorhaben: Technische Universität Hamburg  
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