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Bridge inspection methods using unmanned vehicles have been attracting attention. In this study, we devised an efficient and reliable method for visually inspecting bridges using unmanned vehicles. For this purpose, we developed the BIRD U-Net algorithm, which is an evolution of the U-Net algorithm that utilizes images taken by unmanned vehicles. Unlike the U-Net algorithm, however, this algorithm identifies the optimal function by setting the epoch to 120 and uses the Adam optimization algorithm. In addition, a bilateral filter was applied to highlight the damaged areas of the bridge, and a different color was used for each of the five types of abnormalities detected, such as cracks. Next, we trained and tested 135,696 images of exterior bridge damage, including concrete delamination, water leakage, and exposed rebar. Through the analysis, we confirmed an analysis method that yields an average inspection reproduction rate of more than 95%. In addition, we compared and analyzed the inspection reproduction rate of the method with that of BIRD U-Net after using the same method and images for training as the existing U-Net and ResNet algorithms for validation. In addition, the algorithm developed in this study is expected to yield objective results through automatic damage analysis. It can be applied to regular inspections that involve unmanned mobile vehicles in the field of bridge maintenance, thereby reducing the associated time and cost.

As the global fitness industry rapidly digitalizes, home fitness applications have emerged as a convenient solution for people to exercise anytime, anywhere. This study investigated the mediation effect of exercise satisfaction on the relationship between content characteristics and continuance intention to use home fitness applications. This study provided guidance for developing effective home fitness applications by analyzing which content characteristics can increase the continuance intention to use home fitness applications. The mediation effect of exercise satisfaction on content characteristics and continuance intention to use was examined using a structural equation model analysis, and 330 survey responses from individuals who have used home fitness applications for exercise were analyzed. The results confirmed that the enhancement of the content characteristics exerted a positive effect on exercise satisfaction and continuance intention to use. Additionally, the enhancement of exercise satisfaction characteristics positively affected the continuance intention to use. Further, exercise satisfaction was observed to exert a significant mediating effect on the relationship between the content characteristics and continuance intention to use home fitness applications. These findings suggest that it is essential to devote significant attention to enhancing content characteristics and exercise satisfaction in the development of home fitness applications.