TY - GEN
T1 - BIM, IoT, and Big Data Integration Framework in the Green Building Industry
AU - Qiang, Guofeng
AU - Tang, Shu
AU - Hao, Jianli
AU - Di Sarno, Luigi
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - Building Information Modeling (BIM), the Internet of Things (IoT), and Big Data are widely applied in the green building industry (GBI) due to the fast-paced digital revolution. BIM enables the creation of digital models of buildings, supporting design optimization, construction management, and sustainability assessment. IoT can automatically acquire real-time data on building operations, occupant behavior, and energy consumption through large amounts of intelligent sensors. However, the vast amount of data created and captured by BIM and IoT is only useful with advanced storage and analysis technologies such as Big Data. So far, BIM, IoT, and Big Data integration in the GBI is still in its infancy. Therefore, this research aims to develop a big data based-framework to store and address context-based data from BIM and time-series data from IoT. First, BIM, IoT, and Big Data application in the GBI is presented. Then, the data exchange model of BIM, IoT, and Big Data is demonstrated through the proposed framework. Finally, digital management strategies are provided for decision-makers to improve the energy efficiency of GBI. This framework underpins the knowledge of digital technologies application in the GBI and provides insights for future research domains such as data exchange, smart construction, and energy management. The practical application of the framework can also contribute to GBI's digital transformation and sustainable development.
AB - Building Information Modeling (BIM), the Internet of Things (IoT), and Big Data are widely applied in the green building industry (GBI) due to the fast-paced digital revolution. BIM enables the creation of digital models of buildings, supporting design optimization, construction management, and sustainability assessment. IoT can automatically acquire real-time data on building operations, occupant behavior, and energy consumption through large amounts of intelligent sensors. However, the vast amount of data created and captured by BIM and IoT is only useful with advanced storage and analysis technologies such as Big Data. So far, BIM, IoT, and Big Data integration in the GBI is still in its infancy. Therefore, this research aims to develop a big data based-framework to store and address context-based data from BIM and time-series data from IoT. First, BIM, IoT, and Big Data application in the GBI is presented. Then, the data exchange model of BIM, IoT, and Big Data is demonstrated through the proposed framework. Finally, digital management strategies are provided for decision-makers to improve the energy efficiency of GBI. This framework underpins the knowledge of digital technologies application in the GBI and provides insights for future research domains such as data exchange, smart construction, and energy management. The practical application of the framework can also contribute to GBI's digital transformation and sustainable development.
KW - BIM
KW - Big data
KW - Energy efficiency
KW - Green building
KW - IoT
UR - http://www.scopus.com/inward/record.url?scp=85189527901&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-7965-3_2
DO - 10.1007/978-981-99-7965-3_2
M3 - Conference Proceeding
AN - SCOPUS:85189527901
SN - 9789819979646
T3 - Lecture Notes in Civil Engineering
SP - 15
EP - 23
BT - Towards a Carbon Neutral Future - The Proceedings of The 3rd International Conference on Sustainable Buildings and Structures
A2 - Papadikis, Konstantinos
A2 - Zhang, Cheng
A2 - Tang, Shu
A2 - Liu, Engui
A2 - Di Sarno, Luigi
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd International Conference on Sustainable Buildings and Structures, ICSBS 2023
Y2 - 17 August 2023 through 20 August 2023
ER -
