Education, Science, Technology, Innovation and Life
Open Access
Sign In

The Role of Artificial Intelligence in Construction Management: A Case Study of Smart Worksite Systems

Download as PDF

DOI: 10.23977/jaip.2023.060813 | Downloads: 90 | Views: 1010

Author(s)

Changhao Wang 1

Affiliation(s)

1 Zhanjiang University of Science and Technology, Zhanjiang, Guangdong, China

Corresponding Author

Changhao Wang

ABSTRACT

Over the past few years, the progressive evolution of information technologies, including cloud computing, big data, artificial intelligence, and the Internet of Things, has become increasingly pervasive across diverse sectors of social development. This integration has spurred a widespread shift towards digitization, empowering various industries to embark on a journey toward high-quality development. Through meticulous analysis, this paper explores the profound impact of intelligent site systems on construction management, emphasizing the pivotal role played by artificial intelligence (AI) in augmenting efficiency, optimizing resources, and reinforcing safety protocols. Drawing insights from diverse case studies, the paper elaborates on how AI-driven smart site systems stimulate innovation and reform in the construction sector. By ushering in the era of digitization and intelligence, these systems propel the entire industry towards a technologically advanced future. In the context of this research, a profound understanding emerges of how intelligent construction management systems are instrumental in shaping the evolving landscape of the construction industry, steering it towards not only heightened efficiency but also a more sustainable and technologically integrated future.

KEYWORDS

Artificial Intelligence, Construction Management, Smart Site System, Efficiency Optimization, Resource Management, Safety, Case Analysis

CITE THIS PAPER

Changhao Wang, The Role of Artificial Intelligence in Construction Management: A Case Study of Smart Worksite Systems. Journal of Artificial Intelligence Practice (2023) Vol. 6: 82-88. DOI: http://dx.doi.org/10.23977/jaip.2023.060813.

REFERENCES

[1] Yang Xiaoyi, Li Lihong, Lu Jianxin, et al. Intelligent managementof super-large Multi-Party Cooperation based on BIM Technology .Information Technology of Civil and Building Engineering, 2018,10 (05) :16-24.
[2] Du Xuanfu. Research on BIM based Intelligent Construction Site Management System . Journal of Engineering Technology Research, 2019, 5(20) : 156-157.
[3] Tang Yizhi. Research on BIM based Smart Construction Site Management . Value Engineering, 2019, 39 (01) : 102-104. 
[4] Liu Shouyu, Song Haigang, Zhou Liang, et al. BIM+ Smart Construction Site Fine-grained collaborative management platform architecture . Chongqing Architecture, 2022,21 (03) : 23-25.
[5] Zhang Zhiwei, Cao Wufu, Yuan Lusha, et al. Construction schedule management of pile foundation based on BIM+ Smart Site platform . Urban Rail Transit Research, 2022,25 (01) : 180-185.
[6] Moon H, Kim H, Kamat V R, et al. BIM-based construction scheduling method using optimization theory for reducing activity overlaps.Journal of Computing in Civil Engineering, 2013,29 (3) : 04014048.
[7] Kim K, Walewski J, Cho YK. Multiobjective construction schedule optimization using modified niched pareto genetic algorithm.Journal of Management in Engineering, 2016, 32 (2) : 04015038.
[8] Faghtihi, Vahid, Reinschmidt, et al. Objective-driven and pareto front analysis: Optimizing time, cost, and job-site movements.Automation in Construction, 2016, 69:79-88.
[9] Pan Y, Zhang L. Oles of artificial intelligence in construction engineering and management: A critical review and future trends. Automation in Construction, 2021, 122:103517.
[10] Xu S, Wang J, Shou W, et al. Computer vision techniques in construction: A critical review. Archives of Computational Methods in Engineering, 2020, 28 (5) : 3383-3397.
[11] Han K, Degol J, Golparvar-Fard M. Geometry- and appearance-based reasoning of construction progress monitoring. Journal of Construction Engineering and Management, 2018, 144 (2) : 04017110.
[12] Dimitrov A, Golparvar-Fard M. Vision-based material recognition for automated monitoring of construction progress and generating building information modeling from unordered site image collections. Advanced Engineering Informatics, 2014, 28 (1) : 37-49.
[13] Qureshi AH, Alaloul W S, Manzoor B, et al. Implications of machine learning integrated technologies for construction progress detection under Industry 4.0 (IR 4.0). 2020 Second International Sustainability and Resilience Conference: Technology and Innovation in Building Designs(51154), 2020:1-6.
[14] Wang Z, Zhang Q, Yang B, et al. Vision-based framework for automatic progress honitoring of precast walls by Using surveillance videos during the construction phase. Journal of Computing in Civil Engineering, 2021, 35 (1): 04020056.
[15] Han K K, Golparvar-Fard M. Appearance-based material classification for monitoring of operation-level construction progess using 4D BIM and site photologs. Automation in Construction, 2015, 53: 44-57.
[16] Li M J. Analysis of BIM technology management platform in construction stage of building projects. Housing and Real Estate, 2020, (36): 152+154.

Downloads: 9113
Visits: 246644

Sponsors, Associates, and Links


All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.