INES has completed an innovative pilot project for Spain’s Ministry of Transport and Sustainable Mobility (MITMS), aimed at forecasting the future condition of bridges within the national infrastructure network through advanced analytics. This project marks a significant step towards adopting predictive maintenance, enabling the early detection of critical issues and the optimization of maintenance resources.
In this groundbreaking initiative, INES has leveraged cutting-edge artificial intelligence techniques, specifically machine learning algorithms. These algorithms were powered by a diverse set of data, including an inventory of the studied bridges, condition indices derived from regular primary inspections, as well as traffic patterns, climatic conditions, and environmental factors.
The results of the analysis are highly promising. The system can accurately predict the degradation of bridges, opening new possibilities for the efficient planning of maintenance actions. This, in turn, will allow MITMS to significantly enhance its asset management strategy, ensuring a more cost-effective and proactive approach to infrastructure upkeep.
With over 25 years of experience, INES Ingenieros Consultores stands as a leader in structural engineering and asset management, renowned for its commitment to technological innovation and the resilience of critical infrastructure.
