Advancing Bridge Construction Monitoring: AI-Based Building Information Modeling for Intelligent Structural Damage Recognition

Building Information Modeling (BIM) has emerged as a transformative technology in the construction industry, revolutionizing various aspects of the field. The integration of Artificial Intelligence (AI) techniques with BIM holds significant promise and is gaining momentum in interdisciplinary applications. In China, the construction industry has witnessed notable advancements through the convergence of BIM, AI, and cloud data. However, the current state of intelligent construction technology in China reveals certain limitations that hinder its comprehensive development. This study addresses these challenges by focusing on the design of intelligent recognition algorithms for monitoring structural damage during bridge construction. Previous research has primarily employed classical neural network algorithms, but these approaches have exhibited certain limitations. This paper proposes innovative improvement measures to overcome these limitations and demonstrates their effectiveness through practical arithmetic examples. Furthermore, to enhance the intelligence level of the BIM system, this study integrates the improved neural network recognition algorithm into the BIM framework. The integration enables the BIM system to recognize and assess bridge structure damage efficiently and accurately. The outcomes of this research provide valuable insights into advancing the field of intelligent construction technology, particularly in the context of bridge construction monitoring.