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Machine Learning Based Smart Railway Ticketing System
Details
Railways are an integral means of public transport in India. Nearly 23.07 million people travel through trains daily in India. The major problems experienced by the passengers are undue waiting time at ticket counters for platform tickets and to board the train. Thus, a system is proposed with smart application using RFID tags and IoT to provide an agile and smooth ticketing experience. This system's infrastructure replaces the frameworks of the queue based system and ATM ticketing system. In order to avoid the chaos of platform ticket buyers in ticket counters, this infrastructure provides a separate access by allocating a different pavement to buy the platform tickets. It maintains a manifest of DBMS for check in and checkout of platform ticket users. The RFID tags read the check in and checkout time by scanning tag and ticket fare is generated based on the timing the user has spent in the platform. This framework can be enabled with digital payments such as UPI, Gpay and EDC machine through the created app. In order to ensure, the safety this system is also supported with AI surveillance. Intelligence incorporated in the system identifies the unauthorized objects and fraudulent
Autorentext
Senthilrani concluiu o doutoramento na área de Engenharia de Informação e Comunicação na Universidade Anna Chennai em 2017. Iniciou a sua profissão como professora na Faculdade de Engenharia e Tecnologia do PSNA, Dindigul no ano de 2005. Em 2008, ingressou como professora na Faculdade de EEE no Velammal College of Engineering and Technology, Madurai.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09786202667838
- Genre Elektrotechnik
- Sprache Englisch
- Anzahl Seiten 92
- Größe H220mm x B150mm x T6mm
- Jahr 2020
- EAN 9786202667838
- Format Kartonierter Einband
- ISBN 6202667834
- Veröffentlichung 09.06.2020
- Titel Machine Learning Based Smart Railway Ticketing System
- Autor Senthilrani Shanmugavelu , Ashok Kumar Balasubramanian
- Gewicht 155g
- Herausgeber LAP LAMBERT Academic Publishing