Computer Vision for Construction Progress Monitoring: A Real-Time Object
  Detection Approach
Jiesheng Yang Andreas Wilde Karsten Menzel Md Zubair Sheikh Boris Kuznetsov
Construction progress monitoring (CPM) is essential for effective project
management, ensuring on-time and on-budget delivery. Traditional CPM methods
often rely on manual inspection and reporting, which are time-consuming and
prone to errors. This paper proposes a novel approach for automated CPM using
state-of-the-art object detection algorithms. The proposed method leverages
e.g. YOLOv8's real-time capabilities and high accuracy to identify and track
construction elements within site images and videos. A dataset was created,
consisting of various building elements and annotated with relevant objects for
training and validation. The performance of the proposed approach was evaluated
using standard metrics, such as precision, recall, and F1-score, demonstrating
significant improvement over existing methods. The integration of Computer
Vision into CPM provides stakeholders with reliable, efficient, and
cost-effective means to monitor project progress, facilitating timely
decision-making and ultimately contributing to the successful completion of
construction projects.