Traditional approaches to managing railway infrastructure assets are characterized by fragmented data at various stages of the lifecycle, where information obtained during surveys and construction is often lost by the time the asset is commissioned, reducing the effectiveness of asset management. This article presents an integrated monitoring technology that enables the creation and seamless updating of a railway asset information model based on remote sensing data from unmanned aerial vehicles (UAVs). The results of testing on a 750-meter experimental railway section are presented, confirming the metrological performance of the proposed methods (the error in determining geometric parameters is less than 1%, provided the survey modes are observed). The practical significance of this work lies in the transition from episodic surveys to continuous digital infrastructure monitoring, which is consistent with the "smart railway" concept and the objectives of the Transport Strategy of the Russian Federation.
Sadovskiy et al. (Tue,) studied this question.