Inteli Mant
The main objective of this project is the design and development of an advanced and intelligent railway infrastructure maintenance system, called Inteli‑Mant. Based on information provided by the infrastructure manager and geometric data obtained by the maintenance operator, the system is capable of identifying and predicting maintenance needs across different railway sections. It also prioritizes activities to ensure the highest possible track quality, thereby achieving optimal levels of safety in passenger rail transport, improving service quality, and increasing the productivity of both personnel and machinery assigned to maintenance tasks.
The solution is based on the implementation of data repositories (Data Lakes), Business Intelligence tools, and visualization systems (dashboards), enabling the storage, segmentation, analysis, and visualization of data in a simple manner. This facilitates the optimization of maintenance scheduling, whether for ongoing monitoring, planned tasks, or immediate interventions.
The handling of large volumes of data and historical datasets (Big Data), together with trend analysis (Analytics) and predictive analysis based not only on data trends but also on the system’s continuous learning (Machine Learning), improves decision‑making efficiency and enhances overall service quality. This enables maintenance managers to process track condition data more quickly, monitor the evolution of detected issues, plan corrective actions, and anticipate the emergence of defects that may compromise safety, allowing for the implementation of preventive maintenance strategies.
In summary, the implementation of this solution would provide significant benefits, including improved efficiency in managing large datasets, enhanced quality indicators for Iberovías, better resource allocation and maintenance planning, and a substantial increase in service quality delivered to Adif, as well as improved performance of maintenance teams.
