The integrated use of telecommunications and informatics to remotely monitor and transmit data from railcars and locomotives, including GPS location, temperature, shock events, door open/close status, and mechanical sensor readings. Telematics devices enable proactive management of car condition and cargo integrity without physical inspection. They are increasingly standard on tank cars, refrigerator cars, and high-value equipment.
The use of Global Positioning System receivers installed on locomotives or railcars to provide continuous real-time location data independent of wayside AEI readers. GPS tracking is standard on locomotives and is increasingly deployed on railcars and intermodal containers for enhanced visibility. It provides location data in areas between AEI readers and within yards.
The use of onboard sensors and wayside detectors to continuously assess the mechanical condition of railcars, detecting developing faults such as bearing degradation, wheel flat spots, and brake issues before they cause failures. Car health data is integrated with maintenance planning systems to enable predictive maintenance. It reduces bad-order rates and unplanned service interruptions.
A system of passive RFID tags mounted on every railcar and locomotive and read by wayside readers at strategic locations throughout the network, automatically recording the car number, direction, and time of passage. AEI data is the backbone of real-time car location and train tracking for both operational and customer visibility purposes. The system was mandated by the FRA and deployed network-wide in the 1990s.
The use of machine learning models, historical performance data, real-time train location, and network condition information to generate more accurate arrival time predictions for railcars and intermodal shipments. Predictive ETA models outperform schedule-based estimates by accounting for actual network conditions and train plan changes. Improved ETA accuracy enables better inventory management and customer service.