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Advances in Computer Science and Ubiquitous Computing pp 251–258Cite as

Intelligent Personalized Transport Alert System with Edge Computing

Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 715)

Abstract

Most people’s lives are based on a repetitive routine. Despite this fact, people check information on traffic situations manually using their mobile applications every day. Also, inconveniences may be caused due to unexpected and constantly changing traffic situations that arise from a number of factors. Many services that provide information on traffic, weather, and transportation are available, but there isn’t a system that provides all this information at the same time. As a solution to this problem, we suggest a new notion called Intelligent Personalized Transport Alert System (IPTAS). IPTAS provides information on the transportation mode and the arrival time to users automatically via speech and text notification based on the user’s current location, time, date, weather, and traffic situation. Through IPTAS, convenience in daily life is enhanced, and more accurate information is given to the user.

Keywords

  • Artificial intelligence system
  • Personalized system
  • Public data
  • Real-time android
  • Notification alert system

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References

  1. Jung JaeGon (2019) Do it! Android programming. Easyspublishing, Seoul, Republic of Korea

    Google Scholar 

  2. Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning: data mining, inference, and prediction. Springer, Stanford, California

    CrossRef  Google Scholar 

  3. James G, Witten D, Hastie T, Tibshirani R (2017) An introduction to statistical learning: with applications in R. Springer, Stanford, California

    MATH  Google Scholar 

  4. Sheng QZ, Yu J, Dustdar S (2017) Enabling context-aware web services: methods, architectures, and technologies. CRC Press Florida, Boca Raton

    Google Scholar 

  5. Lim BY, Dey AK (2011) Evaluating intelligibility usage and usefulness in a context-aware application, human-computer interaction. Towards Intell Implicit Interact Part 5:92–101

    Google Scholar 

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Acknowledgements

This work was supported by Institute for Information and communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No.2018-0-01456, AutoMaTa: Autonomous Management framework based on artificial intelligent Technology for adaptive and disposable IoT)

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Authors and Affiliations

  1. Department of Information Technology Engineering, Sookmyung Women’s University, Seoul, South Korea

    Hyolin Choi, Jiwon Hong & Yongik Yoon

Authors
  1. Hyolin Choi
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  2. Jiwon Hong
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  3. Yongik Yoon
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Corresponding author

Correspondence to Hyolin Choi .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science and Technology, Nowon-gu, Korea (Republic of)

    Prof. James J. Park

  2. Faculty of Science, Department of Computer and Information Science, University of Macau, Taipa, Macao

    Prof. Dr. Simon James Fong

  3. Department of Computer Science, Georgia State University, Atlanta, GA, USA

    Prof. Yi Pan

  4. Department of Multimedia Engineering, Dongguk University, Seoul, Korea (Republic of)

    Prof. Yunsick Sung

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Choi, H., Hong, J., Yoon, Y. (2021). Intelligent Personalized Transport Alert System with Edge Computing. In: Park, J.J., Fong, S.J., Pan, Y., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. Lecture Notes in Electrical Engineering, vol 715. Springer, Singapore. https://doi.org/10.1007/978-981-15-9343-7_34

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  • DOI: https://doi.org/10.1007/978-981-15-9343-7_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-9342-0

  • Online ISBN: 978-981-15-9343-7

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