Enabling remote condition monitoring
Cordel solutions offers the ability to perform effective and efficient remote condition monitoring (RCM) on any scale of rail network.
Automate asset inspections and surveys
Using powerful Machine Learning technology developed in real world settings, Cordel enables automated data analysis across entire railway networks.
Keep track of changes and deterioration
Cordel use Machine Learning to map assets, rate conditions, and assess changes on a high frequency basis allowing considerable costs to be saved through efficiency.
Enhanced data-driven decision making
With regular data captures, condition ratings and measured anomalies, analytic condition data can be included in more robust data-driven decision-making processes.
The Cordel Solutions
Transit Space Monitoring
The Cordel platform enables any railroad network to quickly and accurately carry out track clearances, gauging and infringement surveys. Our proprietary data pipelines and machine learning platform automate the most labour-intensive steps in the traditional workflow (processing data and identifying features), enabling us to provide your team with engineering-grade data within hours instead of months.
PTC Asset mapping and change management
The Cordel platform provides networks with the ability to create baseline asset surveys affordably and effectively. At the same time, Cordel provides an easy way to map changes automatically to assets over time. Using best in class Machine Learning and survey lidar, manual asset change requests can be a thing of the past.
Track patrol and inspection verification
Regular track patrols are an essential part of any safe and efficient operating railway. The Cordel platform enables networks to automate manual inspection processes using Lidar and Imagery data from in-service trains. The data is then processed automatically using Machine Learning to generate the inspection reports.
Track & Tie Inspections
Cordel offers a flexible and powerful architecture to assist networks in capturing and processing track-based imagery data with positioning data, using powerful Machine Learning models to improve the accuracy, reliability and usability of track & tie visual condition reporting. Measuring skew and tie spacing allows the system to report on exception of potential defects quickly and affordably.
Ballast Profile Management
Using entire networks worth of survey-grade Lidar and imagery data, the Cordel platform creates ballast profiles every metre. It compares these against idealistic engineering modes and reports via exception any ballast profiles outside the standard, curated ready for review.
Transform your infrastructure inspections
Visit our contact page to get started today or book a demo to give us the opportunity to show you first hand how we enable deeper insights into critical infrastructure.