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@article{163698,
        author = {Prem Kaikade and Rohini Pochhi and Sanket Kapse and Harshal Bawne and Aditya Gudmewar and Shyamal Patil},
        title = {Iot based Railway Accident prevention and Automation},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {11},
        pages = {1887-1890},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=163698},
        abstract = {In Indian Railways is one of the most extensive networks in the world. With comparing to the global standard of reliability and passenger safety, Indian Railways does not measure up. Neglecting timely detection and necessary maintenance results in cracks and faults on railway tracks that seriously question the security of rail transport. The development of cracks is 25% of the track length has prompted for its replacement according to a recent study. Determining tracks manually can be burden as well as not completely accurate because of extensive time demands and a need for qualified personnel. To order to tackle the problem effectively with advanced technology’s solutions based on IOT, we present in this paper an railway track crack detection system. By collecting a significant amount of data it is feasible to achieve localization and tracking for Railway Fault Detection. October 29, 2023, a devastating train collision occurred between the Visakhapatnam-Palasa passenger train and the Visakhapatnam-Rayagada passenger train, leaving a trail of destruction between the towns of Alamanda and Kantakapalle in Andhra Pradesh. The project focuses on preventing railway accidents, optimizing power generation, and introducing automation for improved operational processes.},
        keywords = {Arduino NANO, Ultrasonic sensor, Rectifier, GSM module, HC12 RF module.},
        month = {},
        }