# Interoperability of Digital Tools for the Monitoring and Control of Construction Projects
## 4 Results and Discussion
### Cyber-Physical Systems
#### 4.1.1 Field Data Capture Technologies (FDCT)  
Progress data have encouraged many researchers and practitioners to introduce various data acquisition technologies via digitization and an automated process of continuous and accurate monitoring of all activities. With these technologies, a better diagnosis and prognosis for the whole construction process is facilitated, with a direct impact on the improvement of production capacities [41]. Construction 4.0 proposes automating and digitizing design and construction processes, with a heavy focus on real-time data capture and technology integration in on-site construction. Some of these technologies have already been tried and used in construction, yielding some promising but limited outcomes; hence, Construction 4 is currently being implemented [41]. Technologies have proven their effectiveness in different functions, such as detection, counting, object identification, measurement of execution times and speeds, quality control, site conditions, location and tracking of elements [42]. To automate the tracking of construction progress, several methods can be used with different types of data acquisition; among the most used are imaging techniques and geospatial techniques [33]. These technologies are characterized according to their capture, visualization and/or geospatial pressure capabilities. Vision-based technologies, such as digital imaging, have enabled the development of civil engineering-related applications that aid in the design, construction and maintenance of construction projects [37]. Visual information from regions that are difficult to access can be easily collected; for example, daily photographs arranged in chronological order make it possible to track changes at a construction site. Therefore, there is the possibility to control the oldest state of the stored information, as all of them are collected in a database [43]. Studies using vision-based technologies for progress monitoring can be grouped into three categories: (i) studies on the generation of as-built 3D models integrated with BIM, (ii) studies using image processing and machine learning methods to monitor the construction progress and (iii) studies using unmanned aerial vehicles for autonomous data collection [44]. In recent years, the focus of researchers has been the use of unmanned aerial vehicles (UAVs) or drones that can be employed for photographic surveys to develop accurate three-dimensional models for intelligent monitoring of the construction progress of large-scale projects [45]. The use of unmanned aerial vehicles (UAVs) or drones has captured the attention of researchers and professionals [46]. UAVs can be employed in different uses depending on the types of sensors that are incorporated in the equipment [47]. Using UAVs with a camera sensor, UAVs allow for photographic surveys to develop accurate three-dimensional models for various applications, such as intelligent monitoring of the construction progress of large-scale projects [45; 48], emergency assistance [49] and industrial operations safety monitoring [50; 51; 52]. Figure 4: Key technologies and features of Industry 4.0. Adapted from [8]. It is common for several of these methods, such as laser scanning, photogrammetry and videogrammetry, to generate three-dimensional point clouds, which allow for the construction of as-built models that give the opportunity to identify the progress at a construction site from various angles and, thus, evaluate the current progress of a project. Among these methods, photogrammetry is the most economical and efficient technique for obtaining a 3D point cloud, which is necessary for progress documentation [53]. Additionally, data fusion using overlapping time frames or overlapping location information from multiple sources is possible by matching the same timestamps or locations.