🤖 AI Summary
To address insufficient intelligence in bridge operation and maintenance (O&M) and the disconnection between multi-source heterogeneous data and high-level decision-making, this paper proposes, for the first time, a large language model (LLM)-based agent framework spanning the entire bridge O&M lifecycle—inspection, assessment, decision-making, and maintenance. The framework integrates multimodal sensor data, machine learning models, and LLMs to enable semantic understanding, reasoning-based planning, and tool invocation, thereby closing the perception–cognition–decision loop. We innovatively introduce a “data–semantics–action” coordination mechanism, establishing a new human–AI collaborative O&M paradigm. Furthermore, we systematically analyze feasible implementation pathways, representative application scenarios, and critical challenges—including domain knowledge alignment, real-time constraints, and trustworthy reasoning—for LLMs in bridge O&M. This work provides both theoretical foundations and reusable technical blueprints for intelligent infrastructure O&M.
📝 Abstract
In various industrial fields of human social development, people have been exploring methods aimed at freeing human labor. Constructing LLM-based agents is considered to be one of the most effective tools to achieve this goal. Agent, as a kind of human-like intelligent entity with the ability of perception, planning, decision-making, and action, has created great production value in many fields. However, the bridge O&M field shows a relatively low level of intelligence compared to other industries. Nevertheless, the bridge O&M field has developed numerous intelligent inspection devices, machine learning algorithms, and autonomous evaluation and decision-making methods, which provide a feasible basis for breakthroughs in artificial intelligence in this field. The aim of this study is to explore the impact of AI bodies based on large-scale language models on the field of bridge O&M and to analyze the potential challenges and opportunities it brings to the core tasks of bridge O&M. Through in-depth research and analysis, this paper expects to provide a more comprehensive perspective for understanding the application of intelligentsia in this field.