The tedious and repetitive process of measuring and assessing track condition and the lack of generational exchange among the aging skilled expert staff is generating ever-increasing costs for maintaining rail infrastructure.
The lack of emergence of new revolutionary solutions and decisive response of infrastructure managers to this problem will cause further aggravation of the problem and high financial losses in the near time frame.
Performing track inspections using machine vision instead of manual inspections, significantly simplifying the planning and execution of rail infrastructure maintenance processes with less personel engagement.
Measuring up to 400 km of railway tracks per day (depending on the rolling stock used) – 40 times more than with manual inspection in the same time frame.
Introducing an unprecedented business model that strongly relieves the customer of the personnel and monetary expenses associated with acquiring, maintaining, and operating the system.
Unification of expert knowledge while saving and storing the volatile expertise and replacing it with a digital memory, effecting in remarkably repeatable and reliable defect detection and evaluation with up to 96% accuracy.
Dedicated streamlined application that allows interaction with the system for AI prediction refinement and generating digital reports on the condition of rail infrastructure from preset measurement sections.
Easily adaptable to different types of rolling stock and specific needs of the customer, allowing easy expansion of the system with new functionalities (extension of the analyzed area, creating digital twins, BIM, etc.).
Provide reports from measurements of inspected infrastructure on customer demand in no more than one business day.
