A Data Analysis Framework Based on Cyber-Physical Systems to Support Data-Driven Decision-Making for Construction Sustainability

被引:0
|
作者
Zheng, Wei [1 ]
Yu, Wen-der [2 ]
Le, Yun [1 ]
机构
[1] Tongji Univ, Sch Econ & Management, Shanghai 200092, Peoples R China
[2] Chaoyang Univ Technol, Construct Engn, Taichung 413, Taiwan
来源
IEEE SYSTEMS JOURNAL | 2023年 / 17卷 / 04期
基金
中国国家自然科学基金;
关键词
Costs; Data analysis; Decision making; Sustainable development; Data models; Analytical models; Data mining; Construction sustainability; cyber-physical systems (CPS); data analysis; decision-making; INDUSTRY; 4.0; ON-SITE; PERFORMANCE; INTEGRATION; SIMULATION; MANAGEMENT; PROJECTS; NETWORK; BIM;
D O I
10.1109/JSYST.2023.3275996
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The construction industry has seen significant advances with the rapid development of cyber-physical systems (CPS). However, the dynamic and complex nature of construction projects still presents various engineering problems throughout their lifecycle. Traditional data analysis methods for engineering problems are inefficient due to the difficulty of collecting, processing, and aggregating data from disparate CPS systems. The lack of practical data analysis methods for solving engineering problems severely affects the sustainability of construction projects. This article develops a CPS-based data analysis framework, the spatial, temporal, and dynamic dimensional data analysis framework, which integrates the data analysis process, decision-making methods, and CPS technologies. It aims to facilitate more efficient data-driven decision-making on engineering issues to improve the sustainability of construction projects. The proposed framework has been implemented in a case study of the Shanghai Planetarium project to demonstrate its applicability and effectiveness.
引用
收藏
页码:5239 / 5250
页数:12
相关论文
共 50 条
  • [41] On data-driven decision-making for quality education
    Kurilovas, Eugenijus
    COMPUTERS IN HUMAN BEHAVIOR, 2020, 107
  • [42] The Rapid Adoption of Data-Driven Decision-Making
    Brynjolfsson, Erik
    McElheran, Kristina
    AMERICAN ECONOMIC REVIEW, 2016, 106 (05): : 133 - 139
  • [43] A Framework to handle Big Data for Cyber-Physical Systems
    Rehman, Shafiq Ur
    Hark, Andre
    Gruhn, Volker
    2017 8TH IEEE ANNUAL INFORMATION TECHNOLOGY, ELECTRONICS AND MOBILE COMMUNICATION CONFERENCE (IEMCON), 2017, : 72 - 78
  • [44] SIDEKICK: Genomic data driven analysis and decision-making framework
    Mark S Doderer
    Kihoon Yoon
    Kay A Robbins
    BMC Bioinformatics, 11
  • [45] SIDEKICK: Genomic data driven analysis and decision-making framework
    Doderer, Mark S.
    Yoon, Kihoon
    Robbins, Kay A.
    BMC BIOINFORMATICS, 2010, 11
  • [46] Secure Data Transmission and Trustworthiness Judgement Approaches Against Cyber-Physical Attacks in an Integrated Data-Driven Framework
    Jiang, Yuchen
    Wu, Shimeng
    Yang, Hongyan
    Luo, Hao
    Chen, Zhiwen
    Yin, Shen
    Kaynak, Okyay
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 52 (12): : 7799 - 7809
  • [47] Measuring the performance of connectivity solutions for cyber-physical systems in logistics: a novel framework for decision-making
    Rawat, Umabharati
    Anbanandam, Ramesh
    BENCHMARKING-AN INTERNATIONAL JOURNAL, 2024,
  • [48] A System-of-Systems Framework of Data Analytics to Support Strategic Decision-Making in the Construction Industry
    Nickdoost, Navid
    Choi, Juyeong
    Abdelrazig, Yassir
    CONSTRUCTION RESEARCH CONGRESS 2022: COMPUTER APPLICATIONS, AUTOMATION, AND DATA ANALYTICS, 2022, : 412 - 421
  • [49] Data-Driven Robust Non-Fragile Filtering fot Cyber-Physical Systems
    Lyu, Ming
    Liu, Lei
    Zhang, Jie
    Bo, Yuming
    IEEE ACCESS, 2017, 5 : 19668 - 19679
  • [50] Information Fusion and Data-Driven Processing In Inertial Measurement Units for Cyber-Physical Systems
    Lee, Nelson
    Lyshevski, Sergey Edward
    2017 IEEE 37TH INTERNATIONAL CONFERENCE ON ELECTRONICS AND NANOTECHNOLOGY (ELNANO), 2017, : 438 - 442