A study on the efficiency of bridge inspection report preparation leveraging large language models

Abstract

In the face of the impending decrease in the working-age population, one urgent issue is the streamlining and efficiency improvement of structural inspection in social infrastructure maintenance. In recent years, the use of AI has attracted attention as a solution to this issue, with numerous studies being conducted mainly on image data and waveform data. However, there are still few studies on natural language data. Considering the recent proliferation of conversational AI, this paper examines the streamlining of bridge inspection report creation using large language models. As a result of our investigation, we confirmed that the use of large language models is effective in streamlining the creation of bridge inspection reports.