BIM, IoT, and Big Data Integration Framework in the Green Building Industry

Guofeng Qiang, Shu Tang*, Jianli Hao, Luigi Di Sarno

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationTowards a Carbon Neutral Future - The Proceedings of The 3rd International Conference on Sustainable Buildings and Structures
EditorsKonstantinos Papadikis, Cheng Zhang, Shu Tang, Engui Liu, Luigi Di Sarno
PublisherSpringer Science and Business Media Deutschland GmbH
Pages15-23
Number of pages9
ISBN (Print)9789819979646
DOIs
Publication statusPublished - 2024
Event3rd International Conference on Sustainable Buildings and Structures, ICSBS 2023 - Suzhou, China
Duration: 17 Aug 202320 Aug 2023

Publication series

NameLecture Notes in Civil Engineering
Volume393
ISSN (Print)2366-2557
ISSN (Electronic)2366-2565

Conference

Conference3rd International Conference on Sustainable Buildings and Structures, ICSBS 2023
Country/TerritoryChina
CitySuzhou
Period17/08/2320/08/23

Keywords

  • Big data
  • BIM
  • Energy efficiency
  • Green building
  • IoT

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