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Handling research issues for big data extraction in the application of Internet of Vehicles (IoV)

Author

Listed:
  • Gurpreet Singh Panesar

    (Chandigarh University)

  • Kuldeep Narayan Tripathi

    (Indian Institute of Technology Roorkee)

  • Jyoti L. Bangare

    (Savitribai Phule Pune University)

  • Rahul Neware

    (Høgskulen på Vestlandet)

  • Skanda Moda Gururajarao

    (SJCE, JSS Science and Technology University)

Abstract

Big data is becoming increasingly important in the Internet of Vehicles due to the quick expansion of the Vehicular internet infrastructure as well as the dramatic rise of information units. Big data is receiving a great deal of interest in academia and industries. It substantially assists in the formulation of accurate selections as well as the growth of the firm and industry. Furthermore, data from connected vehicles was seen and public participation in advance area development may benefit from enhanced control. The purpose of this study is to provide a detailed overview of all types of self-review articles generated in the early years. We organized a detailed assessment of the research articles for the purpose of discovering possibilities. As a consequence, the study illustrates how big data may help provide accurate and relevant projections and also a comprehensive review of various techniques, gadgets, and methods for using information in the vehicular IN. This research work introduces the pros and corns of various research works in the field of vehicular internet along with the methodology proposed in these research works. The paper focuses on extraction and decomposing lot of information related to traffic of vehicle interneting.

Suggested Citation

  • Gurpreet Singh Panesar & Kuldeep Narayan Tripathi & Jyoti L. Bangare & Rahul Neware & Skanda Moda Gururajarao, 2022. "Handling research issues for big data extraction in the application of Internet of Vehicles (IoV)," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 751-756, March.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01607-9
    DOI: 10.1007/s13198-021-01607-9
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    References listed on IDEAS

    as
    1. Chirag Sharma & Amandeep Bagga & Bhupesh Kumar Singh & Mohammad Shabaz, 2021. "A Novel Optimized Graph-Based Transform Watermarking Technique to Address Security Issues in Real-Time Application," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-27, April.
    2. Deepak Thakur & Jaiteg Singh & Gaurav Dhiman & Mohammad Shabaz & Tanya Gera & Long Wang, 2021. "Identifying Major Research Areas and Minor Research Themes of Android Malware Analysis and Detection Field Using LSA," Complexity, Hindawi, vol. 2021, pages 1-28, September.
    Full references (including those not matched with items on IDEAS)

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