In this paper, we developed a predictive model of maintenance and repair cost based on the element-level condition state by using information collected through the inspection/diagnosis of individual bridges for use in maintenance strategy analysis. The reliability of the prediction model can be improved through of big data analysis using various factors and additional data.

In order to establish preventive maintenance and to make a reasonable estimate of the required repair cost for bridges, the related history information of the existing bridge inspection and diagnosis was analyzed. It was analyzed that about 75% of the repair costs were required for the pavement, expansion joining, curb, and railings in the service area of bridges.