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Transfer Learning Architecture Approach for Smart Transportation System

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Advanced Informatics for Computing Research (ICAICR 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1575))

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Abstract

An intelligent and smart transportation system aims at effective transportation and mobility usage in smart cities. In recent years, modern transportation networks have undergone a rapid transformation. This has resulted in a variety of automotive technology advances, including connected vehicles, hybrid vehicles, Hyperloop, self-driving cars and even flying cars, as well as major improvements in global transportation networks. Because of the open existence of smart transportation system as a wireless networking technology, it poses a number of security and privacy challenges. Information and communication technology has long aided transportation productivity and safety in advanced economies. These implementations, on the other hand, have tended to be high-cost, customized infrastructure systems. To address these challenges, a novel machine learning method developed for a transportation system is reused for making it more generic and smart for intelligent carriage. This type of transfer learning enables rapid progress on the task with enhanced results. In this work, together with domain adaptation, a novel weighted average approach is used to build models related to the smart transportation system. A smart system comprising of interconnected sensors along with the gateway devices can lead the way to a more efficient, viable and robust city centers. Finally, in this paper also provides a view of current research in smart transportation system along with future directions.

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Authors and Affiliations

  1. Assistant Professor School of Science and Technology, Wenzhou Kean University, Zhejiang, China

    Sujatha Krishnamoorthy

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  1. Sujatha Krishnamoorthy
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Correspondence to Sujatha Krishnamoorthy .

Editor information

Editors and Affiliations

  1. Papua New Guinea University of Technology, Lae, Papua New Guinea

    Ashish Kumar Luhach

  2. Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh Jat

  3. Universiti Malaysia Pahang, Pekan, Malaysia

    Kamarul Bin Ghazali Hawari

  4. University of Eastern Finland, Kuopio, Finland

    Xiao-Zhi Gao

  5. Saint Mary's University, Halifax, NS, Canada

    Pawan Lingras

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Krishnamoorthy, S. (2022). Transfer Learning Architecture Approach for Smart Transportation System. In: Luhach, A.K., Jat, D.S., Hawari, K.B.G., Gao, XZ., Lingras, P. (eds) Advanced Informatics for Computing Research. ICAICR 2021. Communications in Computer and Information Science, vol 1575. Springer, Cham. https://doi.org/10.1007/978-3-031-09469-9_15

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  • DOI: https://doi.org/10.1007/978-3-031-09469-9_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-09468-2

  • Online ISBN: 978-3-031-09469-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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