Adopting AI deep learning technology, the system identifies and archives wagon type, wagon number, rated load, curb weight, volume, conversion length, regular inspection due date, capacity scale (for tank wagons) and container number.
Equipped with diversified data interfaces, high recognition accuracy and rapid response, it is extensively applied to industrial sidings, freight terminals and classification yards to eliminate inaccuracies from manual number logging. It supplies objective human-error-free data on wagon and container dwell time, supporting faster turnover and reduced occupation cycle of wagons and containers.
1. Information Recognition
Identifies gondola, flatcar, covered wagon, tank wagon and other wagon types for single-type or mixed-type passing trains;
Captures wagon marking data and container numbers;
Comes with abundant open data interfaces.
2. Automatic Judgment
Auto-trigger upon train arrival for energy conservation;
Automatic traveling direction identification;
Auto segmentation of individual railcars.
3. Query, Statistics & Administration
Search and locate specific wagons by passing time or wagon ID;
Calculate dwell duration by recording inbound and outbound timestamps of wagons and containers.
4. Comprehensive Information & Ultra-fast Recognition
Collect full wagon specification, body marking and container codes;
Finishes recognition within 1.2 seconds with instant accessible output data.
5. Reliable Data Accuracy
After wagon overhaul, electronic tags may fail updating, while physical markings on wagon body always retain the latest authentic specifications.
6. Superior Recognition Rate
Recognition accuracy reaches no less than 98% and keeps improving continuously via iterative AI learning.
Content Recognized by the Intelligent Railway Freight Car Number Recognition System
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