Development of overflow event detection model using LVLM and accuracy verification using image data during large typhoons

Abstract

In recent years, flood damage caused by heavy rain has become frequent, thus necessitating rapid understanding of levee overflow to respond to disasters promptly and disseminate information to the local area. In this study, we constructed three models that can detect overflow events using large-vision-language models and then clarified the detection accuracy of the developed model using actual data (image data from heavy rainfall caused by Typhoon No. 19, 2019). By performing fine-tuning based on OpenAI’s GPT-4o, we demonstrated the possibility of accurately distinguishing between overflow events and normal times.