Integration and transmission of data from UAVs during monitoring and emergency response on railway infrastructure
Abstract
Integration and transmission of data from UAVs during monitoring and emergency response on railway infrastructure
Incoming article date: 14.08.2025The article explores modern approaches to the integration of image processing algorithms and sensor equipment onboard unmanned aerial vehicles (UAVs) for monitoring and mitigation of emergencies affecting railway infrastructure. The research focuses on methods for efficient interaction with high-resolution optical cameras, LiDAR systems, and GPS modules, as well as on the use of distributed and cloud computing technologies for rapid data processing. Special attention is given to adaptive data compression techniques, caching strategies, and asynchronous message queues, which ensure reliable transmission under limited or unstable communication channels.
The work demonstrates practical integration scenarios using the DJI Mini 4 Pro UAV and the WebODM photogrammetric platform, showing a reduction of preliminary processing time from 45 to 6 minutes and an improvement in georeferencing accuracy from 7.8 m to 1.3 m through the use of GPS-EXIF metadata. Point cloud optimization methods, such as Voxel Grid filtering and Statistical Outlier Removal, are shown to decrease file size from 1.2 GB to 210 MB and reduce processing time from 52 to 17 minutes with minimal loss of accuracy.
The study highlights that combining onboard sensors with advanced processing pipelines significantly improves the timeliness, reliability, and accuracy of railway infrastructure assessments after emergencies. The proposed solutions enable automation of geospatial data workflows, enhance operational decision-making, and optimize resource allocation for recovery operations. The findings are relevant for the development of UAV-based monitoring systems in transportation, urban planning, and critical infrastructure protection.Keywords: UAV, data transfer, distributed computing, LiDAR, WebODM, DJI Mini 4 Pro, infrastructure monitoring, adaptive compression, message queue