Anomaly Detection System Using Digital Image Processing For The Indian Railways

Autor:	Amartya Anshuman, Vedant Tibrewal, Sharmista Shastry, Yogesh Kumar Choukiker
Rok vydání:	2021
Předmět:	Computer science business.industry Digital image processing Computer vision Anomaly detection Artificial intelligence business Fault detection and isolation
Zdroj:	International Journal of Scientific Research in Science and Technology. :186-190
ISSN:	2395-602X 2395-6011
DOI:	10.32628/ijsrst2183186
Popis:	The Indian Railways are the lifeline of India's transport system. Being the fourth largest railway network in the world, it covers the length and breadth of the country. In 2018-19, 23.12 million people and 3.36 million metric tons of freight depended on the railways on a daily basis. They bind the economic life of the country and foster the development of industry and agriculture. However, poor maintenance of the railway tracks has caused several accidents over the years. Derailments due to the presence of faults in railway tracks cause heavy loss of life and railway property. Therefore, timely detection and analysis of these cracks is of utmost importance. This proposal aims at providing a cost effective solution to the problem of fault detection in railway tracks using digital image processing.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::51ace2e32a0e29afca7108ab0e648223 https://doi.org/10.32628/ijsrst2183186 Zobrazit plný text záznamu