Decoding a decade: The evolution of artificial intelligence in security, communication, and maintenance within the construction industry

被引:5
作者
Mai, Thu Giang [1 ,2 ]
Nguyen, Minh [1 ]
Ghobakhlou, Akbar [1 ]
Yan, Wei Qi [1 ]
Chhun, Bunleng [3 ]
Nguyen, Hoa [1 ]
机构
[1] Auckland Univ Technol, Comp Sci & Software Engn Dept, Auckland, New Zealand
[2] Hue Univ, Univ Econ, Hue City, Vietnam
[3] MJ Realties Ltd, Auckland, New Zealand
关键词
Artificial intelligence (AI); AI-driven studies; Digital transformation; Predictive analytics; Technology integration; Construction industry; Security; Communication; Maintenance; SAFETY MANAGEMENT; SYSTEM; TECHNOLOGY; HEALTH; COST; OPTIMIZATION; INTEGRATION; PREVENTION; ACCIDENTS; PROJECT;
D O I
10.1016/j.autcon.2024.105522
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper analyzes the evolution of Artificial Intelligence (AI) in the construction industry from 2014 to 2023, focusing on enhancing security, communication, and maintenance. It combines in-depth analysis of 121 papers with visualizations of 507 articles from major databases such as SCOPUS, IEEE, ACM, Science Direct, and Google Scholar to map AI advancements in construction. The study found that security is established as a mature research domain, whereas communication and maintenance are at comparatively earlier stages of development. Specifically, the analysis reveals a shift from Radio Frequency Identification (RFID) to more sophisticated technologies such as Internet of Things (IoT), Virtual Reality (VR), blockchain, Building Information Modeling (BIM), and digital twins, which significantly improve security. Communication and maintenance have also evolved towards greater digital integration and predictive analytics. The integration of AI innovations with human expertise is emphasized as a strategic direction to enhance decision-making and operational efficiency in construction.
引用
收藏
页数:29
相关论文
共 129 条
[71]   Google Scholar as a tool for discovering journal articles in library and information science [J].
Lewandowski, Dirk .
ONLINE INFORMATION REVIEW, 2010, 34 (02) :250-262
[72]   Developing mobile 2D barcode/RFID-based maintenance management system [J].
Lin, Yu-Cheng ;
Cheung, Weng-Fong ;
Siao, Fu-Cih .
AUTOMATION IN CONSTRUCTION, 2014, 37 :110-121
[73]   Looking and learning: using participatory video to improve health and safety in the construction industry [J].
Lingard, Helen ;
Pink, Sarah ;
Harley, James ;
Edirisinghe, Ruwini .
CONSTRUCTION MANAGEMENT AND ECONOMICS, 2015, 33 (09) :740-751
[74]   A real-time monitoring system for lift-thickness control in highway construction [J].
Liu, Donghai ;
Wu, You ;
Li, Shuai ;
Sun, Yuanze .
AUTOMATION IN CONSTRUCTION, 2016, 63 :27-36
[75]  
Liu N., 2018, IET DOCT FOR BIOM EN, P1, DOI [10.1049/cp.2018.1731, DOI 10.1049/CP.2018.1731]
[76]   Calculation model and bearing capacity optimization method for the soil settlement between piles in geosynthetic-reinforced pile-supported embankments based on the membrane effect [J].
Liu, Zhen ;
Zhang, Aobo ;
Xu, Jiangping ;
Zhou, Cuiying ;
Zhang, Lihai .
PLOS ONE, 2021, 16 (08)
[77]   Influence of Artificial Intelligence in Civil Engineering toward Sustainable Development-A Systematic Literature Review [J].
Manzoor, Bilal ;
Othman, Idris ;
Durdyev, Serdar ;
Ismail, Syuhaida ;
Wahab, Mohammad Hussaini .
APPLIED SYSTEM INNOVATION, 2021, 4 (03)
[78]  
McCarthy J, 2006, AI MAG, V27, P12
[79]   A review of the applications of artificial intelligence and big data to buildings for energy-efficiency and a comfortable indoor living environment [J].
Mehmood, Muhammad Uzair ;
Chun, Daye ;
Zeeshan ;
Han, Hyunjoo ;
Jeon, Gyuyeob ;
Chen, Kuan .
ENERGY AND BUILDINGS, 2019, 202
[80]   Automated staff assignment for building maintenance using natural language processing [J].
Mo, Yunjeong ;
Zhao, Dong ;
Du, Jing ;
Syal, Matt ;
Aziz, Azizan ;
Li, Heng .
AUTOMATION IN CONSTRUCTION, 2020, 113