Skip to main content
SpringerLink
Log in
Book cover

Machine Learning Algorithms for Industrial Applications pp 285–300Cite as

Long Term Evolution for Secured Smart Railway Communications Using Internet of Things

  • Chapter
  • First Online:

Part of the book series: Studies in Computational Intelligence ((SCI,volume 907))

Abstract

The railroads have consistently met hurdles due to maintenance and upkeep issues. The length and scale of the network impedes maintenance. Likewise executing and utilizing new age innovation is not feasible still changes should be made on current frameworks. Internet of things is new age innovation that can be executed inexpensively. This can be actualized by simulating the IoT network in small-scale by utilizing Android application and also 4G LTE systems for real time execution. The proposed system uses various sensors to detect distinctive parameters which are regularly checked via the IoT network. And in case any parameter is triggered the system will automatically stop. Although derailment is imminent due to enormous mass of trains, the effect of the crash can be definitely improved by immediate mediation of IoT network. These systems will likewise lessen the overload on government on maintenance and safety related issues of existing framework with lower expenses. These systems also vulnerable to hacking by external factors and one time password system is also used for security. Real time tracking of parameters from base station allows systems to find train journey details such as average speed and performance parameter.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Chen, S., Xu, H., Liu, D., Hu, B., & Wang, H. (2014). A vision of IoT: Applications, challenges, and opportunities with China perspective. Internet of Things Journal, 1, 349–359.

    Article  Google Scholar 

  2. Martinez, B., Montn, M., Vilajosana, I., & Prades, J. D. (2015). The power of models: Modelling power consumption for IoT devices. IEEE Sensors Journal, 15, 5777–5789.

    Article  Google Scholar 

  3. Kim, J., Choi, S. W., Song, Y. S., Yoon, Y. K., & Kim, Y. K. (2015). Automatic train control over LTE: Design and performance evaluation. IEEE Communications Magazine, 53(10), 102–109.

    Article  Google Scholar 

  4. Song, Y. S., Kim, J., Choi, S. W., & Kim, Y. K. (2016). Long term evolution for wireless railway communications: Test-bed deployment and performance evaluation. IEEE Communications Magazine, 54(2), 138–145.

    Article  Google Scholar 

  5. Fraga-Lamas, P., Fernández-Caramés, T.M., & Castedo, L. (2017). Towards the internet of smart trains: A review on industrial IoT-connected railways. IEEE Sensors Journal, 15.

    Google Scholar 

  6. Jat, D. S., Bishnoi, L. C., & Nambahu, S. (2018). An intelligent wireless QoS technology for big data video delivery in WLAN. International Journal of Ambient Computing and Intelligence (IJACI), 9(4), 1–14.

    Article  Google Scholar 

  7. Mukherjee, D., Das, A.K., Dey, S. (2020). Nature Inspired Computing for Wireless Sensor Networks. Singapore: Springer.

    Google Scholar 

  8. Das, S.K., Samanta, S., Dey, N., Kumar, R. (2020). Design Frameworks for Wireless Networks. Singapore: Springer.

    Google Scholar 

  9. Jayraj, S., Singh, A., & Shree, R. (2011). An assessment of frequently adopted unsecure patterns in mobile ad hoc network: Requirement and security management perspective. International Journal of Computer Applications, 24(9), 0975–8887.

    Google Scholar 

  10. Jayakumar, S. K. V., Singh, J., & Joseph, K. S. (2014). Suitable QoS parameters survey for standard web services & web applications to understand their cloud deployability. International Journal of Computational Intelligence Systems, 4, 1–18.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronics and Communication, Dayananda Sagar Academy of Technology and Management, Bangalore, India

    Shweta Babu Prasad & P. Madhumathy

Authors
  1. Shweta Babu Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. Madhumathy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. Madhumathy .

Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, National Institute of Science and Technology (Autonomous), Berhampur, Odisha, India

    Santosh Kumar Das

  2. School of Computer Science and Engineering, National Institute of Science and Technology (Autonomous), Berhampur, Odisha, India

    Shom Prasad Das

  3. Department of Information Technology, Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

  4. Founder and Head of the Egyptian Scientific Research Group (SRGE), Information Technology Department, Cairo University, Faculty of Computer and Artificial Intelligence, Giza, Egypt

    Aboul-Ella Hassanien

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Prasad, S.B., Madhumathy, P. (2021). Long Term Evolution for Secured Smart Railway Communications Using Internet of Things. In: Das, S., Das, S., Dey, N., Hassanien, AE. (eds) Machine Learning Algorithms for Industrial Applications. Studies in Computational Intelligence, vol 907. Springer, Cham. https://doi.org/10.1007/978-3-030-50641-4_16

Download citation

Publish with us

Policies and ethics

Search

Navigation