Walks around the construction site have long been identified as a vital method for keeping work on schedule and under budget. But there hasn’t been much innovation in this field lately. Clipboards and paperwork were finally replaced by mobile devices and digital progress tracking software in the twenty-first century. However, the procedure still largely relies on information gathered manually on the worksite by diverse industry professionals.
This exposes the procedure to error, which is a feature of every subjective, manual process. The likelihood of good faith readings is further diminished by the fact that contractors, whose salaries frequently depend in significant part on the outcomes of such walk-throughs, have interests that are not aligned with those of the project manager. In other words, a haphazard strategy for construction supervision can be worse than none at all.
All of this clarifies why construction technologists have begun to pay attention to construction progress monitoring, as it presents a chance for builders to acquire a competitive edge. The phrase- automated construction progress monitoring, which relates to technology that does away with manual procedures and human error by automating construction progress monitoring and status updates, has become the focus of research.
Expanding the BIM
These innovations can be seen as a development of building information modelling (BIM). In a 4D virtual environment that incorporates a 3D model and the project schedule, BIM simulates projects. Project managers receive improved reporting thanks to BIM, which combines real-time data, especially progress information gathered from site walkthroughs. However, BIM alone is powerless to change the quality of the progress data that comes in and is the foundation of its models. Automated construction progress monitoring may be beneficial in this situation.
Laser scanning, photogrammetry, and videogrammetry are the three main technologies that are used in practise to enable automated building progress monitoring.
The science of taking measurements from images is known as photogrammetry. In photogrammetry, numerous images of an element captured from various positions are used to compute the element’s three-dimensional coordinates.
In reality, photogrammetry has a branch called videogrammetry. Videogrammery uses pictures taken from video frames to calculate an object’s three-dimensional coordinates. Compared to photogrammetry, it is better at capturing dynamic components. The cost of creating point clouds using the laser scanning technique is typically higher than that of the alternatives, and processing the point cloud data takes a disproportionately long time and trained operators.
Long data processing times and lower-quality photos due to electronic disturbances are two other possible drawbacks. Photogrammetry is frequently the most practical technique for producing as-built point cloud data when time, quality, and cost considerations are taken into account. Nevertheless, the approach used to collect data on the progress of the project at hand should always be chosen in light of its unique characteristics and dynamics.
Moving or stationary cameras can be used for photogrammetry. In a fixed method, cameras installed on the job site are programmed to take pictures of the development of a certain area or project component at regular intervals. After that, the photos are assessed to see if the identified alterations adhere to the 4D BIM model’s suggested plan. 99% accuracy can be attained by integrating image sets from two cameras that are positioned over the same area.
Moving camera photogrammetry processes photos from portable cameras, like mobile phones, and tags important items in their frames using image processing and deep learning algorithms. The automated construction progress management system then assesses these objects’ progress status by comparing the photographs of them over time. According to a 2020 case study, the effectiveness of these image processing algorithms in spotting construction activity depends on the standard of the data labelling.
Construction & UAVs
Research into drone- or UAV-mounted systems is the main source of enthusiasm in the automated construction progress management field. UAVs can be programmed to go along specified routes while taking pictures. After being analysed using image analysis and optimization algorithms, progress images taken by UAVs can be connected with 4D BIM systems.
Recent case studies used to test a UAV-mounted system confirmed that it can successfully conduct automatic progress monitoring for particular targets. A system like this would probably be more efficient and less costly than automated construction progress management handled by robots or autonomous vehicles.
No matter the specific strategy, BIM integration is required. Automated progress monitoring systems may soon be a familiar sight on construction project sites, thanks to recent case study findings and a multitude of industrial applications. Automated building progress monitoring systems still have inefficient and expensive data collection and processing methods as bottlenecks. The development of guidelines and principles for automated construction monitoring systems should continue to be a joint effort between academia and the construction industry, with a particular emphasis on these domains.
