A vision-based approach for automatic progress tracking of floor paneling in offsite construction facilities

Pablo Martinez Rodriguez, Beda Barkokebas, Farook Hamzeh, Mohamed Al-Hussein, Rafiq Ahmad*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Offsite construction is an approach focused on moving construction tasks from traditional jobsites to manufacturing facilities. Improved productivity of construction tasks is paramount in terms of competitiveness and is achieved through the continuous improvement of operations and planning, which often relies on historical data obtained from previous projects. Despite being a common practice, current methods, such as time studies, are not able to capture the changing scenarios resulting from improvements to production. This paper presents a novel approach to automatically detect and track the progress of construction operations by applying a method that combines deep learning algorithms and finite state machines to existing footage captured by closed-circuit television (CCTV) security cameras. Applied in the context of floor panel manufacturing stations, the proposed method examines entire production days recorded by CCTV cameras, while providing the durations of each task, its required resources, and the task efficiency per panel with high accuracy.

Original languageEnglish
Article number103620
Number of pages13
JournalAutomation in Construction
Volume125
Early online date17 Feb 2021
DOIs
Publication statusPublished - 1 May 2021
Externally publishedYes

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