ABSTRACT
This study developed a multimodal approach to data collection and analysis using a specially equipped inspection vehicle. This vehicle integrates high-resolution optical and infrared cameras, vibration sensors, and acoustic sensors to capture comprehensive datasets of road and bridge conditions while operating at approximately 60 km/h. Our object of study is how to gather and preprocess the multimodal data for efficient and effective analysis and enhance the detection of both surface anomalies and subsurface degradations. We employ system invariant analysis technology to monitor anomalies by analyzing changes in the correlations between different types of time series data. This approach enables us to identify subtle infrastructure changes that may not be apparent through traditional single sensor inspection methods.
