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Transportation Management Using IoT

Deep Learning to Predict Various Traffic States

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Deep Learning Technologies for the Sustainable Development Goals

Part of the book series: Advanced Technologies and Societal Change ((ATSC))

Abstract

One of the largest issues in terms of road traffic, transportation costs, car parking, service types, etc., is moving people and basic goods between locations. The transportation system is the foundation of supply chain management, and effective management of the aforementioned issues is referred to as transportation management. The development of the Internet of Things (IoT), which makes ordinary physical things or gadgets smart, has recently attracted a lot of interest. IoT is increasingly being used to control local and international transportation systems. Vehicle-to-vehicle communication is made possible by Industry 4.0, which lowers traffic and, as a result, accidents, congestion, pollution, etc. The Internet of Things (IoT) is used in this chapter to improve the shipping and movement of cars and cargoes across various transportation management segments. It increases the vigilance and level of scrutiny for both the product and human movement. The chapter also discusses how deep learning technologies have recently advanced to handle IoT problems in transportation management.

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Authors and Affiliations

  1. School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India

    Amit Singh

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  1. Amit Singh
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Correspondence to Amit Singh .

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Editors and Affiliations

  1. University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

    Virender Kadyan

  2. University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

    T. P. Singh

  3. University of Port Harcourt, Port Harcourt, Rivers State, Nigeria

    Chidiebere Ugwu

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Singh, A. (2023). Transportation Management Using IoT. In: Kadyan, V., Singh, T.P., Ugwu, C. (eds) Deep Learning Technologies for the Sustainable Development Goals. Advanced Technologies and Societal Change. Springer, Singapore. https://doi.org/10.1007/978-981-19-5723-9_14

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  • DOI: https://doi.org/10.1007/978-981-19-5723-9_14

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