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Conference Paper: Internet of Things (IoT)-Integrated Embodied Carbon Assessment and Monitoring of Prefabricated Buildings

TitleInternet of Things (IoT)-Integrated Embodied Carbon Assessment and Monitoring of Prefabricated Buildings
Authors
Issue Date1-Nov-2022
PublisherIOP Publishing
Abstract

Buildings contribute significantly to carbon emissions over their life cycle. Recently, embodied carbon (EC) accounts for an increasing share of life cycle carbon emissions of new buildings as their energy efficiency is improving. However, traditional methods of data collection and communication from diverse carbon sources such as manual recording lead to low-efficient and prone-to-error estimation of embodied carbon emissions. Therefore, this paper aims to propose an Internet of Things (IoT)-integrated embodied carbon assessment and monitoring system (ECAMS) for prefabricated buildings. This system involves three layers, i.e., of data collection, data communication, and data analysis. To provide a theoretical foundation, the EC assessment model is firstly modified to distribute carbon emissions into twelve construction statuses and at five levels of analysis of prefabricated buildings. IoT sensors including radio frequency identification (RFID), acceleration transducer, and global positioning system (GPS) are employed for automated real-time data collection. IoT data will be communicated with building information modelling (BIM) and carbon assessment software through application programming interfaces (APIs). Laboratory tests were conducted to demonstrate the feasibility of sensor-based data collection and communication. The proposed system facilitates more efficient and accurate estimations of prefabricated buildings' embodied carbon, which should help practitioners to explore effective carbon reduction strategies.


Persistent Identifierhttp://hdl.handle.net/10722/342215

 

DC FieldValueLanguage
dc.contributor.authorXu, Jiayi-
dc.contributor.authorPan, Wei-
dc.contributor.authorTeng, Yue-
dc.contributor.authorZhang, Yang-
dc.contributor.authorZhang, Qiqi-
dc.date.accessioned2024-04-17T03:50:04Z-
dc.date.available2024-04-17T03:50:04Z-
dc.date.issued2022-11-01-
dc.identifier.urihttp://hdl.handle.net/10722/342215-
dc.description.abstract<p>Buildings contribute significantly to carbon emissions over their life cycle. Recently, embodied carbon (EC) accounts for an increasing share of life cycle carbon emissions of new buildings as their energy efficiency is improving. However, traditional methods of data collection and communication from diverse carbon sources such as manual recording lead to low-efficient and prone-to-error estimation of embodied carbon emissions. Therefore, this paper aims to propose an Internet of Things (IoT)-integrated embodied carbon assessment and monitoring system (ECAMS) for prefabricated buildings. This system involves three layers, i.e., of data collection, data communication, and data analysis. To provide a theoretical foundation, the EC assessment model is firstly modified to distribute carbon emissions into twelve construction statuses and at five levels of analysis of prefabricated buildings. IoT sensors including radio frequency identification (RFID), acceleration transducer, and global positioning system (GPS) are employed for automated real-time data collection. IoT data will be communicated with building information modelling (BIM) and carbon assessment software through application programming interfaces (APIs). Laboratory tests were conducted to demonstrate the feasibility of sensor-based data collection and communication. The proposed system facilitates more efficient and accurate estimations of prefabricated buildings' embodied carbon, which should help practitioners to explore effective carbon reduction strategies.</p>-
dc.languageeng-
dc.publisherIOP Publishing-
dc.relation.ispartofCIB World Building Congress 2022 (26/06/2022-30/06/2022, , , Melbourne, Australia)-
dc.titleInternet of Things (IoT)-Integrated Embodied Carbon Assessment and Monitoring of Prefabricated Buildings-
dc.typeConference_Paper-
dc.identifier.doi10.1088/1755-1315/1101/2/022031-
dc.identifier.scopuseid_2-s2.0-85144110655-
dc.identifier.volume1101-
dc.identifier.issue2-

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