AI Computer Vision for Railways

Prevent Train Derailments with Akridata for Railways

Train derailments can incur billions in expenses for railway companies, including costs associated with cleanup, compensation, and freight loss. Use Data Explorer to build, test, and deploy high-accuracy computer vision models that keep your railroad operations on track.

There are more than 1,000 train derailments per year in the United States, resulting in a significant loss of time, money, and — worst of all — lives.

Relying on manual wheel inspections alone is no longer feasible. But even with automation, railway companies struggle to handle the high volume of images from camera inspection waypoints or lack the data needed to train their inspection models.

SOLUTION

Automated Wheel Defect Detection

Problem

Railway companies gather millions of wheel inspection waypoint images. Yet, the shortage of sample data examples hinders effective wheel defect identification, compromising safety and efficiency.

Goal

Prevent derailments by enhancing models with synthetic images to improve the accuracy of defect detection.

Solution

Leverage Akridata to generate hundreds to thousands of synthetic images, enriching your dataset and enhancing your model's accuracy.

See how Akridata can help.

HOW IT WORKS

Integrated Railway Inspection System

Edge Collection & Inference

Data Explorer collects data from the image database associated with your current vision system and uses deep learning to classify the captured images. The software can be easily customized to match your specific environment.

Advanced Wheel Inspection

Utilizing state of the art models, Data Explorer retrieves data from the image database linked to your current vision system, enabling the identification and resolution of wheel variations, cracks, and defects.

Synthesizing Crack Variations for Enhanced Model Reliability

Data Explorer detects pertinent wheel visuals such as cracks and defects, synthesizing hundreds of thousands of data points. This process refines your dataset, simplifying the identification of wheel defects and enhancing the reliability of your model.

Continuous Deployment and Monitoring

As the model encounters increasing common cases with wheel defects, it will continually update to enhance its quality and improve the accuracy of your model.

Need More?

Akridata Visual Data Platform

Don’t have an in-house Data Science team for railway defect detection?

Akridata Edge provides ready-to-use railway models, rigorously tested and refined with millions of train wheel images, ensuring accurate defect detection.

Customer spotlight

Largest freight railroad company achieves 98.5% Model Accuracy

By using Akridata Data Explorer to refine and enhance their computer vision model, the largest freight railroad company increased the accuracy of their wheel inspection model to 98.5%. Additionally, since using Akridata, they have not experienced any instances of real-world wheel cracks that went undetected by the model.

FAQs

How does Akridata help prevent train derailments in the railway industry?

Akridata uses AI-powered computer vision to detect rail defects, including wheel cracks and anomalies. By analyzing visual data in real-time, it helps identify potential issues before they lead to derailments, improving overall rail safety and reducing costly accidents.

What types of defects can Akridata’s Automated Wheel Defect Detection identify?

The automated detection system can identify various wheel defects, such as cracks, damage, and anomalies. It uses edge collection, inference, and deep learning to enhance the accuracy and reliability of rail inspections.

How accurate is Akridata's railway inspection system?

Akridata’s railway inspection system has achieved up to 98.5% model accuracy for defect detection, as demonstrated in its work with leading freight railroad companies. This high level of accuracy ensures efficient and reliable rail operations.

Can Akridata’s solution integrate with existing railway inspection systems?

Yes, Akridata’s Data Explorer can seamlessly integrate with existing rail inspection processes. It collects data from in-line imaging devices and customizes its deep learning models to suit specific operational needs, enhancing defect detection efficiency.

What benefits do railway companies gain from using Akridata's visual data platform?

Railway companies benefit from improved safety, reduced derailment risks, efficient wheel defect detection, and continuous system monitoring. This leads to decreased operational costs, enhanced rail system reliability, and optimized freight and passenger services.

Ready to ensure seamless rail operations?