NLP Logix Case Studies Railroad Asset Identification using Computer Vision

	Railroad Asset Identification using Computer Vision NLP Logix

Railroad Asset Identification using Computer Vision

NLP Logix

Technology Category	Analytics & Modeling - Computer Vision Software Analytics & Modeling - Machine Learning Sensors - Camera / Video Systems
Applicable Industries	Transportation
Applicable Functions	Business Operation
Use Cases	Vehicle Telematics
Challenge	This customer maintains a railroad network consisting of thousands of miles of track across North America. They are regulated by a primary federal agency for the safe operation and maintenance of their network. One of the many requirements is the consistent posting of signage at various locations of their tracks. The customer began capturing video of their rail network a number of years ago and updates it on a continual basis. The challenge is the ability to watch the video and determine if specific signage is in place and if it is in serviceable condition. Read More
About Customer	Large North American Railroad Company Read More
Customer Name	Undisclosed Read More
Solution	The solution that was implemented was the application of computer vision to "view" all of the thousands of miles of track and identify specific signage. NLP Logix adapted its computer vision infrastructure, to be able to train a machine learning algorithm to identify the specific signage along the rail network. The solution was developed and tested within 60-days and proved to be very accurate and much faster than a human viewing the videos. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Computer Vision Software

Analytics & Modeling - Machine Learning

Sensors - Camera / Video Systems

Applicable Industries

Transportation

Applicable Functions

Business Operation

Use Cases

Vehicle Telematics

Challenge

This customer maintains a railroad network consisting of thousands of miles of track across North America. They are regulated by a primary federal agency for the safe operation and maintenance of their network. One of the many requirements is the consistent posting of signage at various locations of their tracks.

The customer began capturing video of their rail network a number of years ago and updates it on a continual basis. The challenge is the ability to watch the video and determine if specific signage is in place and if it is in serviceable condition.

About Customer

Large North American Railroad Company

Customer Name

Undisclosed

Solution

The solution that was implemented was the application of computer vision to "view" all of the thousands of miles of track and identify specific signage.

NLP Logix adapted its computer vision infrastructure, to be able to train a machine learning algorithm to identify the specific signage along the rail network. The solution was developed and tested within 60-days and proved to be very accurate and much faster than a human viewing the videos.

Impact #1	[Data Management - Data Processing] Video data was able to be processed much faster
Impact #2	[Efficiency Improvement - Operation] Assets could be identified much faster

Impact #1

[Data Management - Data Processing]
Video data was able to be processed much faster

Impact #2

[Efficiency Improvement - Operation]
Assets could be identified much faster

Download PDF Version

Overview

Railroad Asset Identification using Computer Vision

Operational Impact