#The railway series android#
#The railway series crack#

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#The railway series crack#

Yong S, Limeng C, Zhiquan Q, Fan M, Zhensong C (2016) Automatic road crack detection using random structured forests. In: 2021 3rd International conference on signal processing and communication (ICPSC)

Thendral R, Ranjeeth A (2021) Computer vision system for railway track crack detection using deep learning neural network. Rajagopal M, Balasubramanian M, Palanivel S (2018) An efficient framework to detect cracks in rail tracks using neural network classifier. Khatawkar N, Bhat D, Kadli N, Veergoudar D, Doddmani S (2015) An ınspection system for detection of cracks on the railway track using a mobile robot. Muralidharan V, Dinesh V, Manikandan P (2015) An enhanced fault detection system for railway track. Int J Adv Res Electr Electron Instr Eng 4(4). George R, Jose D, Gokul TG, Sunil K, Varun AG (2015) Automatic broken track detection using IR transmitter and receiver. Nisthul G, George L, Varghese N, Jose S, John N, Nandhumon KR (2017) Automatic railway track fault detection system. Jha CK, Singh SK, Sainath TT, Sumanth S (2017) Railway track fault detection vehicle. In: 2016 2nd IEEE ınternational symposium on robotics and manufacturing automation (ROMA), Ipoh, pp 1–6

Lad P, Pawar M (2016) Evolution of railway track fault detection system. In: 2017 IEEE region 10 humanitarian technology conference (R10-HTC), Dhaka, pp 524–527 Mahfuz N, Dhali OA, Ahmed S, Nigar M (2017) Autonomous railway fault detector robot for Bangladesh: SCANOBOT. Molodova M, Li Z, Núñez A, Dollevoet R (2014) Automatic detection of squats in railway infrastructure. The data stored on the application is backed up on Firebase real-time database which is a cloud-based solution that keeps data secure from crashes and other intrusion-related threats.

#The railway series android#

The bot has added an Android application interface and SIM-based GSM message communication to provide exact GPS location enabled via Google Maps on a mobile device. It is an IoT-based application of ultrasonic sensors and utilizes an ML model to identify nature of defects in the track and hence ascertain the severity of the defects. An advanced railway track fault detection system (ARTFDS) is intended for monitoring faults in railway tracks. Hence, we need a reliable, accurate and agile method of finding complications in railway tracks as both lives and goods are at stake. The annual ridership of Indian Railways is approximately 9.16 billion with the total length of railway tracks being 1150 billion km, and the total freight/goods transported annually stand at 1.1 billion tonnes. Indian Railways are an integral part of India’s economic ecosystem.