## 5 Application Domain
### Progress Monitoring  
Construction projects can get delayed due to various causes, such as weather, supply chain disruptions, or human error [20]. Projects must be monitored regularly, and corrective actions must be taken to reduce the impact of the delays [20]. Traditionally, the project manager (PM) visits the jobsite to monitor construction operations and compares the as-built state of the construction with as-planned state [171]. It allows project managers to timely identify schedule discrepancies [172]. When the PM cannot visit the site, time-series images that show the progress over time are also used by them for progress monitoring [173]. Typically, this process is manual and strenuous [174; 175; 123]. Automated progress monitoring aims to make this process more efficient and precise through the use of technology such as BIM, robotics, and image processing [171].  
[PERSON] et al. [20] developed a robotic system equipped with LiDAR, wheels, and rotors connected with a remote server for remote progress monitoring. The advantage of such a system is that it saves time for the project manager, as the robotic system moves faster than a human, so can cover a larger area in less time [176; 177]. The PM can monitor multiple projects from one remote location [178]. [PERSON] et al. [179] developed an image stitching algorithm that converts a video captured through a UAV into a sitewide panorama. This allows the PM to view the entire jobsite at one glance and monitor the progress.  
An extension to the above approach is to automatically detect progress from visual data by robots. Computer vision has been used to automatically identify building components (e.g., drywall) from 2D images and update the progress information in an Industry Foundation Classes (IFC)-based 4D Building Information Model (BIM) [169]. Such algorithms used in conjunction with autonomously navigating robotic systems [180; 181] driven by BIMs automate a significant part of progress monitoring, thereby reducing human effort.  
Using point clouds from laser scans is also used to detect constructed elements to measure progress [174]. Since laser scanning is a time-consuming task, using autonomous robots for laser scanning can reduce the human resource requirement. A major challenge in automating the progress monitoring process through visual scans is to identify the optimum points that provide the best view of all constructed elements [174].  
Visualization of construction progress based on information collected by robots needs to be considered too. Human inspectors receive a wealth of contextual information during manual walkthroughs, which helps them understand the construction work. Looking at 2D images is not intuitive for that task [126]. [PERSON] et al. [126] created a methodology for visualizing 360\({}^{\circ}\) images collected on-site using a quadruped robot within a 3D virtual environment created with BIM. The 360\({}^{\circ}\) images were geolocated inside the building using BIM, which provides enough contextual information to understand the image's relationship to the building. Immersive virtual reality has also been tested to assist a remote inspector visualize the site visuals easily and intuitively [178].