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ADiTI™
Automation using Digital Track Inspection
ADiTI™ harnesses computer vision, machine learning, quantum computing, and satellite imaging for automated railway track inspection, detecting and addressing track obstructions and defects around the clock, replacing labour-intensive manual inspection.
Key Features
- Real-time detection and classification of track obstructions and defects
- Comprehensive hazard detection: vegetation encroachment (trees, plants) and flooding risks
- Advanced imaging: satellite and quantum-computing analysis for high-resolution, large-scale threat identification
- Machine learning that continuously learns and improves detection across landscapes and weather
- Seamless integration with existing railway systems for legacy and modern operations
Benefits Over Manual Inspection
- Eliminates human error with precise, objective assessments
- 24/7 monitoring that sharply cuts incident response times
- Lower operational costs and optimised labour resources
- Predictive maintenance that reduces downtime and extends asset lifespan
- Adapts to diverse regions and weather; reduces environmental impact
Advantages of Implementation
- Unmatched reliability as a dependable, data-driven alternative to human supervision
- Faster risk mitigation through real-time alerts and rapid decision-making
- Future-proof technology built on quantum computing and machine learning
Measured Impact
Real-time
Track anomaly detection
24/7
Round-the-clock monitoring
90%
Vegetation non-compliance addressed