For project managers, accurate, timely, and intuitive information is the key to successful decision-making during progress control at a construction site. This paper presents a method that combines computer vision with building information modeling (BIM) for automated progress monitoring of tiles. This method can automatically and accurately measure the in-built progress information of a construction site and transmit real-time progress information to the cloud in a visualized form. With the in-built and real-time progress information, project managers can know the progress of construction site in time and make decisions easily. The proposed method includes several modules. First, an image database is built with thousands of tile images, and a variety of local binary patterns (LBPs) feature extraction methods, and support vector machines (SVMs) are used to train a tile classifier with satisfactory performance, with an accuracy of 91.17%. The purpose of the first module is to construct a mathematical feature of an image and to train a classification algorithm according to this feature, so that tiles in images can be identified. The improved edge detection algorithm detects the boundaries of completed tiles in given images. Afterward, the boundary line coordinates are converted from image pixel coordinates to a real-world coordinate system through camera calibration. Next, using the information from the camera location and room profile information extracted from the BIM model, the actual tile area can be calculated automatically. Finally, the in-built progress is highlighted in the room floor plan, and the result is delivered to the BIM cloud simultaneously. The proposed method was tested at a real indoor construction site. The experimental results indicate that the method can effectively carry out real-time automatic quantity calculations.

Real-time identification and prevention of safety risks in dynamic construction activities are demanded by construction safety managers to cope with the growing complexity of the construction site. Most of the studies on BIM-based construction safety inspection and prevention use data from the planning and design stage. Meanwhile, safety managers still need to spend a lot of time gathering reports about construction safety risks in certain periods or areas from inferred results in BIM. Therefore, this paper proposed an automatic safety risk identification and prevention mechanism for the construction process by integrating a safety rule library based on ontology technology and Natural Language Processing. An automatic inspection mechanism integrating BIM and safety rules is constructed, and a presentation mechanism of intelligent detection results based on Natural Language Processing is designed. The construction process safety rule checking system was developed, and the effectiveness of the system was verified by a case study. The outcome of this paper contributes to the development and application of ontology in construction safety research, and the NLP-based safety rule checking result presentation will benefit safety inspectors and construction managers in practice.

Fire hazard in public buildings may result in serious casualties due to the difficulty of evacuation caused by intricate interior space and unpredictable development of fire situations. It is essential to provide safe and reliable indoor navigation for people trapped in the fire. Distinguished from the global shortest rescue route planning, a framework focusing on the local safety performance is proposed for emergency evacuation navigation. Sufficiently utilizing the information from Building Information Modeling (BIM), this framework automatically constructs geometry network model (GNM) through Industry Foundation Classes (IFC) and integrates computer vision for indoor positioning. Considering the available local egress time (ALET), a back propagation (BP) neural network is applied for adjusting the rescue route according to the fire situation, improving the local safety performance of evacuation. A campus building is taken as an example for proving the feasibility of the framework proposed. The result indicates that the rescue route generated by proposed framework is secure and reasonable. The proposed framework provides an idea for using real-time images only to implement the automatic generation of rescue route when a fire hazard occurs, which is passive, cheap, and convenient.

In the new era of Construction 4.0, the application of a large number of intelligent information technologies (ITs) and advanced managerial approaches have brought about the rapid development of intelligent construction management (ICM). However, it is still unclear how to assess the maturity of ICM. In this study, a maturity assessment system for ICM was formulated through literature reviews, questionnaires, expert discussions and a case study. A maturity scoring table containing five assessment dimensions and twenty assessment indicators was developed, and corresponding maturity levels and a radar chart of dimensions were designed. A case study of the assessments of two construction enterprises was conducted to validate that the proposed assessment system could be used by construction enterprises to quantitatively assess their ICM maturities and obtain both overall and specific assessment results. This study also proposed practical improvement methods to improve ICM maturities for construction enterprises with different maturity levels. Furthermore, the study also discussed the development direction of ICM at present and in the short-term future, which should be paid more attention to by the construction industry.

Construction courses are characterized by a combination of theoretical and practical knowledge; however, the teaching of practical knowledge is often absent due to safety and cost considerations. VR can improve the teaching of practical knowledge by facilitating interactions between teachers and students through virtual means, regardless of location, which is a weakness of current lecture-based teaching, especially in the COVID-19 era. Therefore, this paper aims to evaluate the effect and discuss the prospect of VR in construction teaching, with a comparative study of 50 students who were evenly divided into two groups and taught using traditional teaching and VR teaching, respectively. This experiment shows that VR teaching improves the students’ learning enthusiasm and satisfaction, especially in terms of practical knowledge. Additionally, students believe the combination of traditional and VR teachings can be more helpful in construction teaching. The findings of this research strengthened the advantages of VR in delivering practical knowledge in construction teaching.