Our RailAI solution uses multiple sensors and artificial intelligence to automate all aspects of railroad infrastructure inspection. The RailAI autonomous railcar operates unmanned and provides real-time track condition data for immediate corrective action and the ability to achieve predictive maintenance and data-driven capital planning.
The correctly referenced, repeated run data, collected over time, allows accurate modeling of track components, including tie condition and rail wear, to optimally plan track OE and capital maintenance programs. It additionally provides predictive capabilities to recognize emerging issues for early minor repair, reducing operating costs and risk by minimizing unplanned track outages.
Alerts can contain specific data from the vicinity of the defect, enhancing the notification received by management to enable remote evaluation and dispatch. All raw and processed assessment data belongs to our clients. Field data can be offloaded via Wi‑Fi or manually and provided in client-defined data formats for in‑house or third-party data analytics and asset management.
The game-changing benefits of Tetra Tech’s RailAI autonomous track assessment system will increase as Federal Railroad Administration pilot programs mature to allow autonomous inspection systems to incrementally replace manual inspection methods. The unique onboard real-time processing and reporting capability of the RailAI autonomous track assessment system provides timely identification of defects, supporting the transition to autonomous inspection, and provides the data necessary to optimize asset maintenance and health.