A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Computer vision-based interior construction progress monitoring: A literature review and future research directions
Abstract Computer vision (CV)-based technologies have been used to automate construction progress monitoring. The automation attempts to maximise precision and minimise human intervention in onsite progress monitoring. Such attempts have mainly focussed on exterior construction environments while there are significantly lesser number of studies on interior construction. This imbalance impedes automation of the onsite progress monitoring as a whole. Thus, the core intent of this study is to pave the way for advancing automated indoor progress monitoring by providing a systematic survey of extant literature. Main contributions of this survey include 1) presenting a full spectrum of CV-based approaches, tools, and algorithms adopted for indoor construction progress monitoring (ICPM) 2) portraying a succinct reference to the shortcomings, technical challenges, and scope limitations of the past studies on ICPM. The study then synthesises a readily usable agenda for hybridising CV with other data-driven technologies to improve automation in ICPM.
Graphical abstract Display Omitted
Highlights Significant gap between indoor and outdoor construction in adopting computer vision. Indoor progress monitoring is constrained due to object detection challenges. These challenges are related to indoor objects, lighting conditions and camera movements. Hybridising computer vision with other data-driven technologies is one of the future research directions.
Computer vision-based interior construction progress monitoring: A literature review and future research directions
Abstract Computer vision (CV)-based technologies have been used to automate construction progress monitoring. The automation attempts to maximise precision and minimise human intervention in onsite progress monitoring. Such attempts have mainly focussed on exterior construction environments while there are significantly lesser number of studies on interior construction. This imbalance impedes automation of the onsite progress monitoring as a whole. Thus, the core intent of this study is to pave the way for advancing automated indoor progress monitoring by providing a systematic survey of extant literature. Main contributions of this survey include 1) presenting a full spectrum of CV-based approaches, tools, and algorithms adopted for indoor construction progress monitoring (ICPM) 2) portraying a succinct reference to the shortcomings, technical challenges, and scope limitations of the past studies on ICPM. The study then synthesises a readily usable agenda for hybridising CV with other data-driven technologies to improve automation in ICPM.
Graphical abstract Display Omitted
Highlights Significant gap between indoor and outdoor construction in adopting computer vision. Indoor progress monitoring is constrained due to object detection challenges. These challenges are related to indoor objects, lighting conditions and camera movements. Hybridising computer vision with other data-driven technologies is one of the future research directions.
Computer vision-based interior construction progress monitoring: A literature review and future research directions
Ekanayake, Biyanka (author) / Wong, Johnny Kwok-Wai (author) / Fini, Alireza Ahmadian Fard (author) / Smith, Peter (author)
2021-04-10
Article (Journal)
Electronic Resource
English
Computer vision-based construction progress monitoring
| Elsevier | 2022
Automated Computer Vision-Based Construction Progress Monitoring: A Systematic Review
| DOAJ | 2022