Artificial intelligence and machine learning applications in the project lifecycle of the construction industry: A comprehensive review

被引:9
|
作者
Datta, Shuvo Dip [1 ]
Islam, Mobasshira [1 ]
Sobuz, Md. Habibur Rahman [1 ]
Ahmed, Shakil [1 ,3 ]
Kar, Moumita [2 ]
机构
[1] Khulna Univ Engn & Technol, Dept Bldg Engn & Construct Management, Khulna 9203, Bangladesh
[2] Patuakhali Sci & Technol Univ, Dept Entomol, Dumki 8602, Patuakhali, Bangladesh
[3] HawarIT Ltd, Dhaka, Bangladesh
关键词
Artificial intelligence; Machine learning; Project lifecycle; Construction industry; Construction management; IoT; BUILDING DEMOLITION WASTE; AUGMENTED REALITY; BIBLIOMETRIC ANALYSIS; DIGITAL TWIN; BIM; ENERGY; MANAGEMENT; TECHNOLOGY; OPPORTUNITIES; AUTOMATION;
D O I
10.1016/j.heliyon.2024.e26888
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The construction industry faces many challenges, including schedule and cost overruns, productivity constraints, and workforce shortages. Compared to other sectors, it lags in digitalization in every project phase. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies revolutionizing the construction sector. However, a discernible gap persists in systematically categorizing the applications of these technologies throughout the various phases of the construction project life cycle. In response to this gap, this research aims to present a thorough assessment of the deployment of AI and ML across diverse phases in construction projects, with the ultimate goal of furnishing valuable insights for the effective integration of these intelligent systems within the construction sector. A thorough literature review was performed to identify AI and ML applications in the building sector. After scrutinizing the literature, the applications of AI and ML were presented based on a construction project life cycle. A critical review of existing literature on AI and ML applications in the building industry showed that AI and ML applications are more frequent in the planning and construction stages. Moreover, the opportunities for AI and ML applications in other stages were discussed based on the life cycle categorization and presented in this study. The practical contribution of the study lies in providing valuable insights for the effective integration of intelligent systems within the construction sector. Academically, the research contributes by conducting a thorough literature review, categorizing AI and ML applications based on the construction project life cycle, and identifying opportunities for their deployment in different stages.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] Machine Learning and Artificial Intelligence Applications in Building Construction: Present Status and Future Trends
    Ensafi, Mahnaz
    Alimoradi, Saeid
    Gao, Xinghua
    Thabet, Walid
    CONSTRUCTION RESEARCH CONGRESS 2022: COMPUTER APPLICATIONS, AUTOMATION, AND DATA ANALYTICS, 2022, : 116 - 124
  • [32] Special Issue Review: Artificial Intelligence and Machine Learning Applications in Remote Sensing
    Chen, Ying-Nong
    Fan, Kuo-Chin
    Chang, Yang-Lang
    Moriyama, Toshifumi
    REMOTE SENSING, 2023, 15 (03)
  • [33] Applications of artificial intelligence and machine learning image analyses in dermatology: a systematic review
    Choy, Shern-Ping
    Paolino, Alexandra
    Kim, Byung Jin
    Lim, Sarah Man Lin
    Seo, Jessica
    Tan, Sze Ping
    Tan, Wei Ren
    Corbett, Mark Stephen
    Barker, Jonathan N. W. N.
    Lynch, Magnus D.
    Smith, Catherine H.
    Mahil, Satveer K.
    BRITISH JOURNAL OF DERMATOLOGY, 2022, 187 : 129 - 129
  • [34] Applications and perspectives of artificial intelligence, machine learning and "dentronics" in dentistry: A literature review
    Mayta-Tovalino, Frank
    Munive-Degregori, Arnaldo
    Luza, Silvia
    Cardenas-Marino, Flor
    Guerrero, Maria
    Barja-Ore, John
    JOURNAL OF INTERNATIONAL SOCIETY OF PREVENTIVE AND COMMUNITY DENTISTRY, 2023, 13 (01): : 1 - 8
  • [35] Artificial intelligence and machine learning in ophthalmology: A review
    Srivastava, Ojas
    Tennant, Matthew
    Grewal, Parampal
    Rubin, Uriel
    Seamone, Mark
    INDIAN JOURNAL OF OPHTHALMOLOGY, 2023, 71 (01) : 11 - 17
  • [36] Exploring the Impact of Artificial Intelligence and Machine Learning in the Diagnosis and Management of Esthesioneuroblastomas: A Comprehensive Review
    Patel, Raj
    Masys, Tadas
    Baridi, Refat
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2024, 16 (06)
  • [37] Advances in Artificial Intelligence, Machine Learning and Deep Learning Applications
    Haleem, Muhammad Salman
    ELECTRONICS, 2023, 12 (18)
  • [38] Clinical Applications of Artificial Intelligence, Machine Learning, and Deep Learning in the Imaging of Gliomas: A Systematic Review
    Alhasan, Ayman S.
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2021, 13 (11)
  • [39] Applications of artificial intelligence and machine learning approaches in echocardiography
    Nabi, Wafa
    Bansal, Agam
    Xu, Bo
    ECHOCARDIOGRAPHY-A JOURNAL OF CARDIOVASCULAR ULTRASOUND AND ALLIED TECHNIQUES, 2021, 38 (06): : 982 - 992
  • [40] Artificial intelligence and machine learning | applications in musculoskeletal physiotherapy
    Tack, Christopher
    MUSCULOSKELETAL SCIENCE AND PRACTICE, 2019, 39 : 164 - 169