Computer vision and IoT research landscape for health and safety management on construction sites

被引:23
作者
Arshad, Sameen [1 ]
Akinade, Olugbenga [2 ]
Bello, Sururah [1 ]
Bilal, Muhammad [1 ]
机构
[1] Univ West England UK, Big Data Enterprise & Artificial Intelligence Lab, Frenchay Campus, Bristol BS16 1QY, England
[2] Teesside Univ, Ctr Digital Innovat, Sch Comp Engn & Digital Technol, Dept Comp & Games, Middlesbrough TS1 3BX, England
基金
“创新英国”项目;
关键词
BEHAVIOR-BASED SAFETY; NEURAL-NETWORKS; FRAMEWORK; WORK;
D O I
10.1016/j.jobe.2023.107049
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Aims: Perform a systematic review of current literature to evaluate and summarise the health and safety hazards on construction sites. Methods: Science Direct, SCOPUS and web of science databases were searched for research articles published from 2013 to 2021. From an initial search of 350 research articles, we removed the duplicate articles and carried out an analysis of the abstract and full text that focused on health, safety, hazards, behaviour, on-site health and safety and the digital technologies leaving a total of 66 studies included.Results: Computer vision and Internet of Things (IoT) are the dominant technologies for health and safety management. A comparison of the two technologies reveals that computer vision is dominant because of its non-intrusive approach to data collection; thus, supporting the scalability of computer vision approach at the expense of cost and development time. It will help to prevent on-site health and safety hazards and injuries on construction site. Conclusion: Computer vision offers non-intrusive benefits over Internet of Things (IoT); being able to detect the health and safety hazards. Com-puter vision has proved to be beneficial for better accuracy prediction, real time data monitoring, and model development for onsite health and safety analytics on the construction site.
引用
收藏
页数:12
相关论文
共 87 条
[1]  
Alamgir M.B., 2021, IRASD J COMPUT SCI I, V2, P40
[2]   A Domain Ontology for Software Requirements Change Management in Global Software Development Environment [J].
Alsanad, Abeer Abdulaziz ;
Chikh, Azeddine ;
Mirza, Abdulrahman .
IEEE ACCESS, 2019, 7 :49352-49361
[3]   Personal protective equipment (PPE) usage in construction projects: A scientometric approach [J].
Ammad, Syed ;
Alaloul, Wesam Salah ;
Saad, Syed ;
Qureshi, Abdul Hannan .
JOURNAL OF BUILDING ENGINEERING, 2021, 35
[4]   Scene understanding in construction and buildings using image processing methods: A comprehensive review and a case study [J].
Arashpour, Mehrdad ;
Tuan Ngo ;
Li, Heng .
JOURNAL OF BUILDING ENGINEERING, 2021, 33 (33)
[5]  
Awolusi I, 2019, COMPUTING IN CIVIL ENGINEERING 2019: DATA, SENSING, AND ANALYTICS, P530
[6]   Predicting the Occurrence of Construction Disputes Using Machine Learning Techniques [J].
Ayhan, Murat ;
Dikmen, Irem ;
Birgonul, M. Talat .
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2021, 147 (04)
[7]   Privacy Preserving Blockchain Technique to Achieve Secure and Reliable Sharing of IoT Data [J].
Bao Le Nguyen ;
Lydia, E. Laxmi ;
Elhoseny, Mohamed ;
Pustokhina, Irina, V ;
Pustokhin, Denis A. ;
Selim, Mahmoud Mohamed ;
Gia Nhu Nguyen ;
Shankar, K. .
CMC-COMPUTERS MATERIALS & CONTINUA, 2020, 65 (01) :87-107
[8]  
Blagec K., 2021, ARXIV
[9]   Quality Control in Systematic Reviews and Meta-analyses [J].
Bown, M. J. ;
Sutton, A. J. .
EUROPEAN JOURNAL OF VASCULAR AND ENDOVASCULAR SURGERY, 2010, 40 (05) :669-677
[10]   The dual effects of the Internet of Things (IoT): A systematic review of the benefits and risks of IoT adoption by organizations [J].
Brous, Paul ;
Janssen, Marijn ;
Herder, Paulien .
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2020, 51