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Smart Transportation Tracking Systems Based on the Internet of Things Vision

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Connected Vehicles in the Internet of Things

Abstract

In recent years, people have pursued smarter and faster options for fast-paced modern lifestyles. This is in response to many technologies that have recently emerged. Vehicle tracking systems based on the Internet of Things (IoT) technology is one of these. This chapter aims to examine the IoT-based cutting-edge vehicular tracking systems. For this purpose, 30 peer-reviewed research publications, from 2014 to 2018, were selected and raw data was extracted. Selection was based on certain critical parameters such as: measuring attributes of the moving vehicle, sensors and actuators used for data obtaining in tracking devices, data transferring methods for transmission, networks and protocols utilized for communication, utilized stock for data storage, programming languages or systems, and algorithms utilized for raw data analysis. The investigation demonstrated that (i) a large portion of the IoT sensors and actuators were centered on the primary location tracking system in cloud data centers that can be handled remotely by retrieving real-time data, (ii) The GPS sensors widely use in vehicle tracking systems were based on the RFID technology, (iii) Wi-Fi networks were the most popular networks while GSM/GPRS and TCP/UDP protocols were the best transport layer protocols, (iv) most used storage method was observed as the cloud for smart vehicle tracking systems, and (v) Kalman filter was the most popular algorithm in vehicular tracking systems. Moreover, the most critical advantage of using IoT for tracking systems was the effectiveness, security, and intrusion of protection for the passengers. The security administration could monitor students by remotely tracking their RFID sensor tags or any IoT sensor embedded in the tracking unit. This chapter also reviews and provides relevant information for road traffic officers and related experts, correspondence technologists, and technological innovation researchers on the IoT-based smart vehicle tracking frameworks.

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Author Contribution and Acknowledgements

U.F and M.N.H conceived the idea of the study and developed the analysis plan. U.F analyzed the data and developed the initial paper. M.N.H helped to prepare the figures and tables and finalized the manuscript. R.S completed the final editing of the manuscript. All authors read the finalized manuscript.

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Authors and Affiliations

  1. School of Computing and Mathematics, Charles Sturt University, Melbourne, VIC, 3000, Australia

    W. K. A. Upeksha K. Fernando & Ruwani M. Samarakkody

  2. Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC, 3010, Australia

    Malka N. Halgamuge

Authors
  1. W. K. A. Upeksha K. Fernando
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  2. Ruwani M. Samarakkody
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  3. Malka N. Halgamuge
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Corresponding author

Correspondence to Malka N. Halgamuge .

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Editors and Affiliations

  1. Debesis Education, Littleover, Derby, UK

    Zaigham Mahmood

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Fernando, W.K.A.U.K., Samarakkody, R.M., Halgamuge, M.N. (2020). Smart Transportation Tracking Systems Based on the Internet of Things Vision. In: Mahmood, Z. (eds) Connected Vehicles in the Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-030-36167-9_7

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  • DOI: https://doi.org/10.1007/978-3-030-36167-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36166-2

  • Online ISBN: 978-3-030-36167-9

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