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Ferrovial Recognised for the Implementation of Drones and Artificial Intelligence in Infrastructure


  • Civildron2020, the largest Spanish congress in the drone industry, has awarded Ferrovial the first prize in its annual competition

  • This app represents a significant improvement in current inspection processes, reducing the risk or exposure for maintenance workers


Ferrovial Power Infrastructure, in collaboration with Ferrovial’s Digital Hub, has developed a transmission line inspection platform with the use of drones and artificial intelligence. This project has already been implemented in the company’s assets in Chile. The platform represents a significant improvement in current inspection processes, reducing the risk or exposure for maintenance workers, as well as reducing the time and cost of inspections.

Civildron2020, the largest Spanish congress in the drone industry, has awarded Ferrovial the first prize in its annual competition. This recognition highlights the relevance of the solution developed by Ferrovial, which combines two cutting-edge technologies: drones and artificial intelligence. It is also a recognition of the efforts of Ferrovial Power Infrastructure to seek innovative solutions, as well as to the company’s commitment to the safety of its employees. The platform has been developed to run in the cloud. This allows it to be scalable and open to the incorporation of other infrastructures, drones, sensors and artificial intelligence models of its own or of third parties, covering all stages of the inspection life cycle:

  • Planning, recording and evaluating inspection work (calendar, area to be inspected, required documentation on pilots and drones …)

  • Evaluation of the mission, definition of the process and approval

  • Execution of the flight and registration on the platform of all the captured data and images

  • Automatic identification of anomalies or potential points of failure through the use of integrated artificial intelligence models

  • Automatic reporting of any detected incidents

  • Information management and access to it from multiple platforms and devices

The Project has the following advantages copared to the current model:

  • Automatic identification and quantification of anomalies thanks to artificial intelligence algorithms

  • Significant increase in the accuracy of anomaly detection thanks to the use of different sensors

  • Digitization of all the captured information to be able to make comparisons over time

  • Significant reduction in the risk of accidents by maintenance workers

  • Time and resources optimization for asset maintenance tasks

  • Over 40% cost savings

With this new development, Ferrovial has improved the safety of its workers and increased the quality of the maintenance of its assets, gaining a competitive advantage for the company

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