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  4. Cloud and edge computing to enable map overlays for the digitalization of construction sites
 
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Cloud and edge computing to enable map overlays for the digitalization of construction sites

Publikationstyp
Conference Paper
Date Issued
2024-07
Sprache
English
Author(s)
Resapow, Valentin
Stührenberg, Jan  
Digitales und autonomes Bauen B-1  
Schwall, Michael
Chillón Geck, Carlos  
Digitales und autonomes Bauen B-1  
Smarsly, Kay  
Digitales und autonomes Bauen B-1  
TORE-URI
https://hdl.handle.net/11420/50360
Start Page
315
End Page
324
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-s2.0-85207181661
Construction sites are typically characterized by inherent complexity, unstructured environments, dynamic changes, and susceptibility to environmental factors. Previous efforts to visualize events and processes at construction sites have been hampered by the absence of appropriate digital site representations. While virtual reality has received a lot of attention for visualizing construction sites, the integration of real-time information has rarely been explored. This study aims to integrate the cloud and edge computing paradigms to generate real-time map overlays of sites. The map overlays are updated by data collected from sensors mounted on machines operating on the construction site. Different overlays deployed to improve sustainability, safety, and efficiency are implemented and validated at the Volvo Construction Equipment GmbH test facility in Konz, Germany. The results show that the cloud and edge computing paradigms and the map overlays provide a solid foundation for real-time visualization and digitalization of construction sites.
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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