| Abstract [eng] |
Master thesis work is dedicated to the construction of an automatic information system managing time and price in construction, particularly of high-speed railway bridges. This system combines various advanced tools to contribute to project management efficiency, such as 3D modelling with Revit, automation with Dynamo scripts, centralised data storage with SQL Server, and project progress and resource allocation visualization in real-time with Power BI. AI tools as ChatGPT API are integrated for reporting automation and decision making. The approach resolves issues like matching the Bill of Quantities (BOQ) with 3D object models, full synchronization of real-time data and automating singular known structures, such as anti-uplift guided bearings. It ensures efficiency, helps avoid mistakes, and can update the project schedule and cost dynamically. Through the validation of this system with a real-life railway bridge project, this research shows that the system can be applied to the future infrastructures and illustrates the scalability of the system. The master thesis also recommends building on the proposed system towards lifecycle automation, sustainability integration, advanced AI applications, and agile data interoperability within the construction industry. |
