Application research of deep learning-based BIM Technology in Intelligent Construction

With the increasing importance of energy-efficient renovations in architecture, the pressing issue of how to enhance the effectiveness of such renovations through advanced technology has come to the forefront. This article affirms the significance of building information modeling (BIM) technology in energy consumption renovations. It introduces a BIM-based building energy monitoring system, which not only provides comprehensive and effective static information for energy consumption analysis but also offers real-time visualization of energy consumption status for daily management. By collecting all necessary data for energy management and storing it in the cloud, this system greatly facilitates data analysis. Moreover, the article proposes a short-term electricity load forecasting method for community buildings based on empirical mode decomposition (EMD)-gated recurrent unit (GRU). The EMD-GRU method proposed in this article exhibits superior accuracy compared to other methods, with a mean absolute percentage error value of 14.43%. By considering factors such as historical load, weather, and date, this method accurately predicts short-term electricity loads for communities. This research provides a robust framework for improving energy management in buildings through advanced technologies, ultimately leading to more effective energy-saving renovations and optimizations.