Recently, the application of the BIM technique to infrastructure lifecycle management has increased rapidly to improve the efficiency of infrastructure management systems. Research on the lifecycle management of infrastructure, from planning and design to construction and management, has been carried out. Therefore, a systematic review of the literature on recent research is performed to analyze the current state of the BIM technique. State-of-the-art techniques for infrastructure lifecycle management, such as unmanned robots, sensors and processing techniques, artificial intelligence, etc., are also reviewed. An infrastructure BIM platform framework composed of BIM and state-of-the-art techniques is then proposed. The proposed platform is a web-based platform that contains quantity, schedule (4D), and cost (5D) construction management, and the monitoring systems enable collaboration with stakeholders in a Common Data Environment (CDE). The lifecycle management methodology, after infrastructure construction, is then completed and is developed using state-of-the-art techniques using unmanned robots, scan-to-BIM, and deep learning networks, etc. It is confirmed that collaboration with stakeholders in the CDE in construction management is possible using an infrastructure BIM platform. Moreover, lifecycle management of infrastructure is possible by systematic management, such as time history analysis, damage growth prediction, decision of repair and demolition, etc., using a regular inspection database based on an infrastructure BIM platform.

Facility data is created throughout the design and construction phase. But the most facility managers bear significant costs that arise from the lack of interoperability with facility lifecycle. This paper is concerned with the way to collect facility data using BIM technology. The aim of this paper is to suggest BIM data modeling guide for the facility management using the information that need to be delivered from design and construction phase to operation and management phase. The BIM data modeling guide focus on the properties of mechanical equipment. It is to be hoped that this study will contribute to collect facility data from as-built BIM data and to build facility management system database without difficulty.

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There is the difference of criteria to apply guidelines among the project participants and to depend on the purpose of utilizing BIM models, although modeling criteria are basically provided through BIM guidelines. Therefore, it is quite important to check compliance with guidelines to raise quality of the BIM model. But Quality Checking (QC) items and method for BIM model modeled in accordance with guidelines is not provided. This study suggested QC items and Rule Specifications(RS) for automatic QC. First of all, QC items were derived by analyzing domestic BIM guidelines and a process for structuring natural language is conducted by utilizing flowchart and pseudocode. So, by combining them, RS was suggested. Finally, RS-based case study was conducted by implementing automatic QC process with solibri model checker TM. This study will contribute to the improvement of design quality and completeness of BIM model including huge data of 3 dimension. Furthermore, it is necessary to develop BIM guidelines according to the use case and to provide detailed process and standard for QC of BIM model.