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ADVANCED RAILWAY TRACK FAULT DETECTION AND REPORTING OVER INTERNET OF THINGS (IOT)
Authors
RNLS Kalpana,M. Vamshitha,M. Niharika,N. Venkatesh
Downlaod Center
Keywords
IoT, NodeMCU ESP32, Ultrasonic sensor, IR Sensor.
Abstract
Indian Railways is the largest railway network in Asia and additionally world's second largest network operated underneath a single management. Due to its large size it is difficult to monitor the cracks in tracks manually. This paper deals with this problem and detects cracks in tracks with the help of ultrasonic sensor attached to moving robot. Ultrasonic sensor allows the device to moves back and forth across the track and if there is any fault, it gives information to the cloud server through which railway department is informed on time about cracks and many lives can be saved. This is the application of IoT, due to this it is cost effective system. This effective methodology of continuous observation and assessment of rail tracks might facilitate to stop accidents. This methodology endlessly monitors the rail stress, evaluate the results and provide the rail break alerts such as potential buckling conditions, bending of rails and wheel impact load detection to the concerned authorities. Here we proposed an innovative approach to detect railway track crack as this system detects crack based on image processing. Many image preprocessing steps is used to detect railway track crack. As image is prone to noise. System converts image to grayscale image and uses filtering to remove noise from image. Noise removal helps to detect crack more accurately. Image luminous level is increased and image is converted to binary image. This helps system to detect only crack and helps to remove other unwanted objects. Image once converted to binary image, holes are filled by using image processing method this helps to reject all smaller objects which are not required for crack detection. Crack is detected based on the intensity value. Intensity value is for accuracy.
IJCRT's Publication Details
Unique Identification Number - IJCRT2304658
Paper ID - 234560
Author type - Indian Author
Page Number(s) - f350-f355
Pubished in - Volume 11 | Issue 4 | April 2023
DOI (Digital Object Identifier) -
No Of Downloads - 176
Author Country - India, 501301, Hyderabad, Hyderabad, 501301, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
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RNLS Kalpana,M. Vamshitha,M. Niharika,N. Venkatesh, "ADVANCED RAILWAY TRACK FAULT DETECTION AND REPORTING OVER INTERNET OF THINGS (IOT)", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 4, pp.f350-f355, April 2023, Available at :http://www.ijcrt.org/papers/IJCRT2304658.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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