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Digital Ticketing System for Public Transport in Mexico to Avoid Cases of Contagion Using Artificial Intelligence

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Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1 (FTC 2022 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 559))

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Abstract

In this project, a proposal is made to contribute to the reduction of COVID-19 infections, investigating how to carry out an electronic and/or digital collection system for public transport in Tijuana in Mexico, in addition to having a more versatile intelligent system for users. This proposal also seeks to reduce soil contamination, using fewer physical inputs. Due to the development of the pandemic that has occurred in recent years, there have been thousands of people infected by the COVID-19 virus (SARS-CoV-2). Due to its rapid spread, it has caused many deaths. Alternatives have been sought to seek the reduction of infections. The objective is to reduce the physical entrances to avoid contagions by manipulation to the touch; the transport routes have been contemplated and the different routes in the locality will be analyzed through artificial intelligence and implement it in all public transport routes. Also a system can be implemented for digital ticket.

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Authors and Affiliations

  1. Maestría en Tecnologías de Información, Tecnológico Nacional de México campus Tijuana, Av Castillo de Chapultepec 562, Tomas Aquino, 22414, Tijuana, B.C., Mexico

    Jose Sergio Magdaleno-Palencia, Bogart Yail Marquez, Ángeles Quezada & J. Jose R. Orozco-Garibay

Authors
  1. Jose Sergio Magdaleno-Palencia
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  2. Bogart Yail Marquez
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  3. Ángeles Quezada
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  4. J. Jose R. Orozco-Garibay
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Corresponding author

Correspondence to Jose Sergio Magdaleno-Palencia .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Magdaleno-Palencia, J.S., Marquez, B.Y., Quezada, Á., Orozco-Garibay, J.J.R. (2023). Digital Ticketing System for Public Transport in Mexico to Avoid Cases of Contagion Using Artificial Intelligence. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1. FTC 2022 2022. Lecture Notes in Networks and Systems, vol 559. Springer, Cham. https://doi.org/10.1007/978-3-031-18461-1_24

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