Artificial Intelligence for Remote Monitoring

Project information

  • Acronym: AI R Monitoring
  • Artificial Intelligence for Remote Monitoring
  • Project director: Christian Chavanel
  • Project manager: Francisco Marques Nunez
  • Status: ongoing project
  • Project code: 2018/RSF/591

Project description

Improving the efficiency of the existing railways assets using the possibility of the new digital possibility, especially the IoT (internet of thinks) and Artificial Intelligence possibility
To reduce in a significative proportion the most important maintenance costs using the new possibilities possibly bring by the new digital technologies
To increase in a significative proportion the line capacity and/or facilitates the operation management using the new possibilities possibly bring by the new digital technologies
To preserve the high investments made in the past to equip line with expensive assets
All measures should be improving the functionalities of the existing assets to make their functioning cheaper and more effective

Improving the IMs and/or RUs assets monitoring by an top effective remote monitoring
The safe functioning of the infrastructures assets (near the track) induce generally cyclic preventive maintenance operations (on the site maintenance) to check their ability to fulfil their obligations. All measures should be taken to improve the availability of the assets and to reduce the maintenance operation need:

  • Improving the efficiency of the existing railways assets using the possibility of the new digital possibility, especially the IoT (internet of thinks) and Artificial Intelligence possibility
  • Improving the IMs and/or RUs assets monitoring by an effective remote monitoring / especially in the POCs 2016 domains: “Switches and Level crossing Remote monitoring with Pattern recognition”, “Insulated Joint real time insulation measurement”, “Closing delay regulation for automatic level crossing automats”, “Pseudo track circuit with train detection, positioning, speed estimation” …

Creating the condition of an effective predictive maintenance based on a real-time information of the maintenance and/or operation teams: the remote monitoring with a data storage of sensors signals and an artificial intelligence treatment of these signals c

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Monday 1 January 2018
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