In the Architecture, Engineering, and Construction (AEC) industry, virtual environments are being utilized to enhance communication among stakeholders and improve visual comprehension. However, stakeholders possess diverse personal characteristics which can affect their spatial recognition ability in virtual spaces. Despite the potential impact of these individual traits, related research still needs to be more comprehensive. Therefore, this study analyzed how each individual’s characteristics influence spatial recognition in a Building Information Model (BIM)-based virtual environment. A quantitative methodology via a survey was employed to investigate the influence of personal factors such as age, gender, education level, and gaming experience on spatial recognition. In a 3D virtual corridor using BIM software, 76 participants were asked to navigate the corridor using a controller and count 23 sprinklers. Of the 76 participants, 30 responses were selected for the statistical analysis. The results demonstrate that age, gender, and education level did not significantly affect spatial recognition in the virtual environment. Conversely, participants with gaming experience tended to perceive spaces in the virtual environment more accurately and realistically, showing a statistically significant difference. This outcome suggests that gaming experience is crucial in enhancing spatial recognition ability in virtual environments. The findings from this study offer critical insights into the impact of individual characteristics on spatial recognition, providing valuable information for the future practical use of BIM-based virtual environments, and can subsequently assist in discovering efficient communication methods among stakeholders.

Concrete infrastructure is vulnerable to damage such as spalling. Spalling leads to chloride penetration, which causes internal corrosion, weakens structural stability and durability, and increases the likelihood of additional cracks or damage, consequently necessitating repair. Existing repair methods do not consider the factors that affect damage in the repaired areas, so additional damage can occur, making monitoring necessary to identify these factors. Nevertheless, existing studies have not adequately addressed the monitoring of internal conditions within concrete, making it difficult to manage such damage effectively. Accordingly, in this study, a monitoring system was developed using building information modeling (BIM) and the Internet of Things (IoT) to better identify internal changes in concrete pavements. Employing embedded sensors to measure temperature, humidity, and stress within the concrete, our system uses Dynamo scripts for real-time data visualization within BIM. Validated against the ASTM D8292 standard, this system captures and analyzes environmental impacts on concrete. This integration facilitates the detection of internal changes, allowing for the real-time visualization of these impacts. This study can help establish repair plans by identifying factors affecting concrete, contributing to preventive maintenance, potentially reducing maintenance costs, and enhancing the sustainability of concrete infrastructures.

Recent advancements in sensor technology have led to an increase in embedding sensors into construction materials for monitoring purposes in the construction industry. However, systematic research on the resulting changes to the material properties is still lacking. A previous study confirmed that the copper–nickel-plated housing of SHT-31 sensors affects the compressive strength of mortar. Moreover, it is necessary to conduct further research to determine if this analogous occurrence takes place in concrete. This study embedded temperature–humidity sensor housings in concrete at 10 mm, 20 mm, and 30 mm, before performing compression tests and a finite element analysis (FEA). The empirical findings indicate that the compressive strengths of concrete at 10 mm, 20 mm, and 30 mm depths were 26.1 MPa, 28.4 MPa, and 29.4 MPa, respectively. In contrast, the control concrete that did not have a sensor housing had a compressive strength of 31.9 MPa. In the case of mortar, a design strength of 28 MPa was achieved at a depth greater than 30 mm, while concrete reached this design strength at 20 mm. Based on these findings, embedding temperature–humidity sensor housings in concrete is recommended at depths greater than 20 mm from the surface. These results serve as important reference data for determining the optimal embedding depth of sensor housings in structures using cement-based materials.

Embedded sensors are widely employed for the structural health monitoring of structures constructed with concrete or mortar. Despite embedded sensors being actively used, there has been no study on whether or not the sensor probe placement within structures made of concrete or mortar influences their structural stability. The strength of small structures in particular could be affected by sensor probes embedded within them. To address the lack of research in this area, this study analyzed the effect of embedding positions of sensor probes on the compressive strength development of mortar. After the production of mortar specimens with the depth of the embedded sensor being controlled by the developed mold, compressive strength tests were conducted, and then test results were verified through finite element analysis. For testing, copper–nickel-plated sensor probes were embedded within the mortar because these sensor probes are popular commercial probes. The test results show that the compressive strength was 7.1 MPa when the sensor probe was embedded at a depth of 5 mm. In contrast, the compressive strength was 28.2 MPa at a depth of 30 mm. Since the compressive strength without the embedded sensor probe was 29.8 MPa, considering the results of this study, it is highly recommended that copper–nickel-plated sensor probes be embedded at least 30 mm from the surface of mortar structures.