Dubai [UAE], August 17 (ANI/WAM): The Automated Railway Infrastructure Inspection System (ARIIS), introduced by Dubai’s Roads and Transport Authority (RTA), serves as a practical model for applying advanced artificial intelligence technologies in the transport sector. The system is designed to enhance the efficiency of operational maintenance, improve safety standards, and reduce reliance on traditional inspections that previously consumed significant time and resources.
This innovative technology represents a major advancement in Dubai Metro’s operational maintenance, aligning with the city’s vision to be a global leader in artificial intelligence and sustainable infrastructure. ARIIS, a sophisticated robotic platform equipped with sensors, lasers, and 3D cameras, autonomously inspects rail tracks and critical infrastructure without interrupting metro operations.
The AI-driven inspection solution enables proactive maintenance strategies through advanced diagnostic technologies, extending infrastructure lifespan and reducing periodic maintenance costs by up to 25 percent. Real-time data analytics further support precise maintenance decisions, improving resource management efficiency by 40 percent and minimizing unnecessary interventions.
Since its introduction, ARIIS has reduced the time required for periodic inspections by 75 percent—equivalent to nearly 1,700 human working hours—and cut traditional inspection operations by up to 70 percent. It has also improved infrastructure condition assessments by 40 percent, accelerating maintenance procedures, reducing emergency interventions, and enhancing overall reliability of the metro network.
The RTA stated that ARIIS is being phased in across select metro lines, with plans to roll it out across all routes following successful technical and operational evaluation. The Authority also confirmed it is exploring the use of ARIIS, or similar technologies, for other transport modes such as trams, depending on infrastructure and operational requirements.
The system collects detailed data on rail conditions, cracks, wear and tear, and deviations, which are analyzed using AI algorithms to enable predictive maintenance. This approach promotes infrastructure sustainability and extends service life.
All inspections are conducted in line with the highest occupational safety standards, coordinated with the control center, and scheduled during nightly maintenance windows to minimize disruptions to metro operations and passenger services. With this technology, inspections are faster and more accurate, eliminating the need to suspend or delay services.
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