Embedded Files
Introduction
Introduction
A system designed using Raspberry pi 4, Arduino mega,DC geared motors to perform railway safety monitoring operation.Haar cascade classifer is used to detect the ROI in each frame.Detection is followed by returning location Co-ordinates of faults,A failure report and an image highlighting the faulty region in HTML.A linear regression based mathematical model is developed by using machine learning for predicting the crack formation and thereby estimating the age of the railway track.
Objectives
Objectives
1. To detect the cracks, present anywhere in the railway track.
2. To provide the location of the crack.
3. To provide a detailed report of the crack.
4. To provide data to the Crack prediction model.
5. To alert before the failure of track and to save passengers lives
6. To eradicate derailment and to enhance safety in railway networks.
7. To Minimize labor and to make the monitoring Autonomous
8. To reduce human error and enhance productivity and life safety.
Working flow diagram
Working flow diagram
Page updated
Google Sites
Report abuse