Deep learning-based computer vision in project management: Automating indoor construction progress monitoring
Progress monitoring is crucial for effective project management, particularly in construction projects. The adoption of computer vision with deep learning expedites automation, accuracy, and efficiency in construction progress monitoring by overcoming the challenges of laborious, and error prone man...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Project Leadership and Society |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666721524000346 |
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| _version_ | 1850110977902641152 |
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| author | Biyanka Ekanayake Johnny Kwok Wai Wong Alireza Ahmadian Fard Fini Peter Smith Vishal Thengane |
| author_facet | Biyanka Ekanayake Johnny Kwok Wai Wong Alireza Ahmadian Fard Fini Peter Smith Vishal Thengane |
| author_sort | Biyanka Ekanayake |
| collection | DOAJ |
| description | Progress monitoring is crucial for effective project management, particularly in construction projects. The adoption of computer vision with deep learning expedites automation, accuracy, and efficiency in construction progress monitoring by overcoming the challenges of laborious, and error prone manual methods. While there is growing attention on developing computer vision based deep learning models for construction progress monitoring, deployment platforms for project managers are lacking. Using computer vision, this study develops a Mask Recurrent Convolutional Neural Network deep learning model. It utilizes progress images of drywall construction from two indoor construction sites and tests the model on a third indoor site in Sydney, Australia. The model is capable of automated as-built visual detection and work-in-progress measurement. The study also provides an understanding on the deployment process of the deep learning model on a cloud-based platform called Streamlit. By developing a model tailored for automatically quantifying work-in-progress of indoor construction elements and detailing the process of deploying that model on a cloud-based platform, this study significantly advances digitalization of construction project management. Project managers, stand to benefit from these advancements by gaining access to more accurate and automated construction progress monitoring for better decision-making. |
| format | Article |
| id | doaj-art-d408ccc3d5ce49f79b99f36ef1ed76f5 |
| institution | OA Journals |
| issn | 2666-7215 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Project Leadership and Society |
| spelling | doaj-art-d408ccc3d5ce49f79b99f36ef1ed76f52025-08-20T02:37:42ZengElsevierProject Leadership and Society2666-72152024-12-01510014910.1016/j.plas.2024.100149Deep learning-based computer vision in project management: Automating indoor construction progress monitoringBiyanka Ekanayake0Johnny Kwok Wai Wong1Alireza Ahmadian Fard Fini2Peter Smith3Vishal Thengane4School of Built Environment, University of Technology Sydney, 15 Broadway, Ultimo, NSW, 2007, Australia; Corresponding author.School of Built Environment, University of Technology Sydney, 15 Broadway, Ultimo, NSW, 2007, AustraliaSchool of Built Environment, University of Technology Sydney, 15 Broadway, Ultimo, NSW, 2007, AustraliaSchool of Built Environment, University of Technology Sydney, 15 Broadway, Ultimo, NSW, 2007, AustraliaSchool of Computer Science and Electronic Engineering, Alan Turing Building, University of Surrey, Guildford, Surrey, United KingdomProgress monitoring is crucial for effective project management, particularly in construction projects. The adoption of computer vision with deep learning expedites automation, accuracy, and efficiency in construction progress monitoring by overcoming the challenges of laborious, and error prone manual methods. While there is growing attention on developing computer vision based deep learning models for construction progress monitoring, deployment platforms for project managers are lacking. Using computer vision, this study develops a Mask Recurrent Convolutional Neural Network deep learning model. It utilizes progress images of drywall construction from two indoor construction sites and tests the model on a third indoor site in Sydney, Australia. The model is capable of automated as-built visual detection and work-in-progress measurement. The study also provides an understanding on the deployment process of the deep learning model on a cloud-based platform called Streamlit. By developing a model tailored for automatically quantifying work-in-progress of indoor construction elements and detailing the process of deploying that model on a cloud-based platform, this study significantly advances digitalization of construction project management. Project managers, stand to benefit from these advancements by gaining access to more accurate and automated construction progress monitoring for better decision-making.http://www.sciencedirect.com/science/article/pii/S2666721524000346Computer visionConstruction projectsDeep learningDigitalizationIndoor construction progress monitoringProject management |
| spellingShingle | Biyanka Ekanayake Johnny Kwok Wai Wong Alireza Ahmadian Fard Fini Peter Smith Vishal Thengane Deep learning-based computer vision in project management: Automating indoor construction progress monitoring Project Leadership and Society Computer vision Construction projects Deep learning Digitalization Indoor construction progress monitoring Project management |
| title | Deep learning-based computer vision in project management: Automating indoor construction progress monitoring |
| title_full | Deep learning-based computer vision in project management: Automating indoor construction progress monitoring |
| title_fullStr | Deep learning-based computer vision in project management: Automating indoor construction progress monitoring |
| title_full_unstemmed | Deep learning-based computer vision in project management: Automating indoor construction progress monitoring |
| title_short | Deep learning-based computer vision in project management: Automating indoor construction progress monitoring |
| title_sort | deep learning based computer vision in project management automating indoor construction progress monitoring |
| topic | Computer vision Construction projects Deep learning Digitalization Indoor construction progress monitoring Project management |
| url | http://www.sciencedirect.com/science/article/pii/S2666721524000346 |
| work_keys_str_mv | AT biyankaekanayake deeplearningbasedcomputervisioninprojectmanagementautomatingindoorconstructionprogressmonitoring AT johnnykwokwaiwong deeplearningbasedcomputervisioninprojectmanagementautomatingindoorconstructionprogressmonitoring AT alirezaahmadianfardfini deeplearningbasedcomputervisioninprojectmanagementautomatingindoorconstructionprogressmonitoring AT petersmith deeplearningbasedcomputervisioninprojectmanagementautomatingindoorconstructionprogressmonitoring AT vishalthengane deeplearningbasedcomputervisioninprojectmanagementautomatingindoorconstructionprogressmonitoring |