This paper is published in Volume 3, Issue 3, 2018
Area
Computer Science
Author
Rijoy Paul
Co-authors
Nima Varghese, Unni Menon, Shyam Krishna K
Org/Univ
Sahrdaya College of Engineering and Technology, Kodakara, Kerala, India
Pub. Date
20 March, 2018
Paper ID
V3I3-1163
Publisher
Keywords
Raspberry Pi 3, Camera, Image Processing, Ultrasonic Sensors, Crack Detection

Citationsacebook

IEEE
Rijoy Paul, Nima Varghese, Unni Menon, Shyam Krishna K. Railway Track Crack Detection, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARnD.com.

APA
Rijoy Paul, Nima Varghese, Unni Menon, Shyam Krishna K (2018). Railway Track Crack Detection. International Journal of Advance Research, Ideas and Innovations in Technology, 3(3) www.IJARnD.com.

MLA
Rijoy Paul, Nima Varghese, Unni Menon, Shyam Krishna K. "Railway Track Crack Detection." International Journal of Advance Research, Ideas and Innovations in Technology 3.3 (2018). www.IJARnD.com.

Abstract

Railways provide the cheapest and most convenient mode of passenger transport both for long distance and suburban traffic. Also, most of transport in India is being carried out by railway network. Still accidents are the major concern in terms of railway track crossing and unidentified crack in rail tracks in Indian railway. About 60% accidents are occurring at railway track crossing and due to crack in railway tracks resulting in loss of precious life and loss of economy. Therefore there is need to think about new technology which is robust, efficient and stable for both crack detection in railway track and object detection. This paper proposes faulty rail track detection and object detection system. This project discusses on a Railway track crack detection using image processing and is a dynamic approach which combines the use of GPS tracking system and WIFI module to send alert messages and geographical coordinate of location. A Raspberry Pi 3 is used to control and coordinate the activities of these devices. This project prevents train derailment by detecting crack in railway track using internet of things technology.
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