Name: Machine Learning Based Smart Railway Ticketing System (en Inglés)
Price: 73.53 USD
Availability: InStock
Author: Shanmugavelu, Senthilrani ; Balasubramanian, Ashok Kumar
ISBN: 9786202667838

portada Machine Learning Based Smart Railway Ticketing System (en Inglés)

Machine Learning Based Smart Railway Ticketing System (en Inglés)

Formato

Libro Físico

Autor

Senthilrani Shanmugavelu

Ashok Kumar Balasubramanian

Editorial

LAP Lambert Academic Publishing

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 0.6 cm

Peso

0.15 kg.

ISBN13

9786202667838

Categorías

Ingeniería electrónica

Machine Learning Based Smart Railway Ticketing System (en Inglés)

Senthilrani Shanmugavelu (Autor) · Ashok Kumar Balasubramanian (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Machine Learning Based Smart Railway Ticketing System (en Inglés)"

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