The Roads and Transport Authority in Dubai launched the Automated Rail Infrastructure Inspection System (ARIIS) as a practical model for employing artificial intelligence to improve operational maintenance efficiency and enhance safety, while reducing reliance on traditional time- and resource-consuming inspections, according to the UAE’s WAM agency.

The agency explained that the system enables the application of proactive maintenance strategies through advanced diagnostic technologies, contributing to extending the infrastructure’s lifespan and reducing periodic maintenance costs by up to 25%. Real-time data analytics support precise decision-making, enhancing resource management efficiency by 40% and limiting unnecessary interventions.

The system’s implementation helped reduce periodic inspection time by 75%, equivalent to about 1,700 human work hours, and cut traditional inspections by 70%, while increasing the infrastructure condition assessment capability by 40%. This also accelerated maintenance procedures, reduced emergency interventions, and improved the metro network’s reliability.

The authority indicated that the system is currently being activated gradually in some metro line areas, with plans to generalize it across all routes and study the possibility of applying it to other transport modes such as trams, according to their infrastructure nature and operational needs.

The system collects comprehensive data on rail conditions, cracks, corrosion, and deviations, analyzing them using AI algorithms to support the concept of predictive maintenance, which enhances infrastructure sustainability and extends its lifespan.