There are different technologies available for smart construction progress monitoring, such as drones, photogrammetry, laser scanning, etc. However, utilization is typically limited due to high costs, complexities, and human resource requirements. This paper presents a framework utilizing the concept of videography through a low-cost Internet protocol (IP) camera and its integration with Matrix Laboratory (MATLAB) and Building Information Modeling (BIM). The integration was done through MATLAB’s tools and programming to develop a software interface. The integration of the IP camera and the developed software allowed for automatic as-built quantity extraction for the concreting in columns, concreting in beams, and block masonry, which were the bulk construction activities. As-planned quantities were imported to the MATLAB interface to compare with as-built quantities, hence providing progress comparative assessment. For instance, the as-planned quantity for column B6 was 20.630 cft. After analysis, the result was 91.5%, which was the percentage completion of the as-built quantity in comparison to the as-planned quantity. Similarly, for beam B1, the as-planned quantity was 13.7 cft, while the as-built quantity was 13.67 cft, which showed 99.8% completion of the activity for beam B1. This study aims to provide different mathematical models for the image processing of the as-built quantities of the construction activities. In addition, this study provides a framework for smart progress monitoring, which can be easily used on the construction sites by the contractors, while also providing paths for future work in developing cost-effective methods for progress monitoring.

有多种可用于智能建筑进度监控的技术，例如无人机，摄影测量，激光扫描等。但是，由于成本高，复杂性和人力资源需求，使用通常受到限制。本文介绍了一个通过低成本互联网协议（IP）摄像机利用摄像概念的框架，并将其与矩阵实验室（MATLAB）和建筑信息模型（BIM）集成。集成是通过MATLAB的工具和编程来完成的，以开发软件界面。IP摄像机和已开发的软件的集成，使得可以自动提取列混凝土，梁中混凝土和砌体这些大宗建筑活动的竣工量。计划数量被导入到MATLAB界面中，以便与建造数量进行比较，从而提供进度比较评估。例如，B6列的计划数量为20.630 cft。经过分析，结果是91.5％，这是完工数量与计划数量相比完成的百分比。同样，对于梁B1，按计划的数量为13.7英尺，而按建造量为13.67英尺，这表明梁B1的活动完成了99.8％。本研究旨在为建筑活动的竣工量图像处理提供不同的数学模型。此外，这项研究还提供了智能进度监控的框架，承包商可以轻松地在建筑工地上使用，