Processing high-volume geospatial data: A case of monitoring heavy haul railway operations

Sensor technology such as GPS can be used in the mapping of transportation networks (e.g., road, rail). However, GPS suffers from errors in positional accuracy due to factors such as signal arrival time. In railway systems, positional accuracy is of utmost importance to identify state of track and wagons for safety and maintenance. Along with GPS, the numerous lightweight sensors installed in each wagon produce a high-velocity geospatial data that needs to be processed continuously and the traditional data processing and storage applications can not handle it. We propose efficient algorithms and a suitable data structure to achieve rapid and accurate location mappings. Our large-scale evaluation demonstrates that the system is accurate and capable of real-time performance.