Self-Organizing Optimization of Construction Project Management Based on Building Information Modeling and Digital Technology

Si, Jennie; Chen, Wan; Hou, Lei; Qu, Yue; Lu, Yanhui; Chen, Taiyu; Yang, Kai

doi:10.1007/s40996-023-01121-x

Cited by 4 publications

(1 citation statement)

References 28 publications

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“…Using the model, the requirements for the amount of energy that the building requires for the two distinct occupancy profiles were estimated. The findings of the simulation imply that the behaviors of the building's inhabitants and the surrounding conditions both have an influence on the potential predictability of the building's flexibility (20).…”

Section: Literature Reviewmentioning

confidence: 90%

Application of Bayesian models in building information modeling of residential buildings

Na Li

2024

jes

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This paper lays forth a process for continuing Bayesian calibration of full-scale building energy simulation (BES) models by making use of data obtained from building information modeling (BIM) and building energy management systems (BEMS). According to a survey taken in China, it is possible that importing data from BIM and BEMS will dramatically cut down on the amount of time and effort required for the continuing calibration of BES models. After that, the continuous calibration approach that had been developed was examined with the use of a case study that was based on the actual calibration of a building. In China, Building Information Modeling (BIM) and data on the amount of electricity used each month over the course of the preceding three years were both incorporated into the case study. According to the findings, a non-continuous technique on the test dataset fared worse than a continuous Bayesian calibration method in terms of prediction accuracy and reduced uncertainty. The normalized mean biased error (NMBE) and the coefficient of variation of the root mean square error (CVRMSE) are both discussed in this research, and comparisons are drawn between the two.

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Section: Literature Reviewmentioning

confidence: 90%

Application of Bayesian models in building information modeling of residential buildings

Na Li

2024

jes

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Factors Analysis of Intelligent Construction Technology Adoption Barriers for Expressway Construction Enterprises

Zhou,

Su,

Zheng

et al. 2024

Iran J Sci Technol Trans Civ Eng

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Digital twin for sustainable development in building automation

Zhang,

Jiang

2024

ECAM

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PurposeThis study investigates the impact and role of digital twin technology in building automation (DTBA) from a sustainability viewpoint. It aims to enhance the understanding of how DTBA can boost efficiency, optimize quality and support sustainable practices in contemporary construction. By exploring the integration of DTBA with sustainable practices, the study seeks to demonstrate how DT can revolutionize building management and operations, leading to significant improvements in resource efficiency, environmental impact and overall operational excellence.Design/methodology/approachThis research employs a bibliographic analysis and systematic review of 176 publications from the past five years (January 1, 2019 to December 31, 2023), focusing on the application and development of DTBA. The study methodically analyzes current trends, identifies research gaps and suggests future directions by synthesizing data from various studies, offering a comprehensive overview of the current state of DTBA research. The approach combines quantitative and qualitative analyses to provide robust insights into the advancements and challenges in the field.FindingsThe review identifies key development areas in DTBA, such as energy and environmental management, resource utilization within a circular economy and technology integration and interoperability. It highlights the necessity for further research to maximize DTBA’s potential in sustainable building automation. The findings suggest that while significant progress has been made, there is a critical need for innovations in data interoperability, predictive analytics and the integration of renewable energy sources to fully realize the benefits of DTBA in enhancing building sustainability.Originality/valueThis paper provides a thorough review of DTBA from a sustainability perspective, offering valuable insights into its current applications and future development potential. It serves as a crucial resource for researchers and practitioners looking to advance sustainable practices in the construction sector using DT technology. By bridging the gap between theoretical research and practical applications, the paper underscores the transformative potential of DTBA in driving sustainable development and provides a roadmap for future research and innovation in the field.

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Self-Organizing Optimization of Construction Project Management Based on Building Information Modeling and Digital Technology

Cited by 4 publications

References 28 publications

Application of Bayesian models in building information modeling of residential buildings

Application of Bayesian models in building information modeling of residential buildings

Factors Analysis of Intelligent Construction Technology Adoption Barriers for Expressway Construction Enterprises

Digital twin for sustainable development in building automation

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