IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v13y2022i1d10.1007_s13198-021-01607-9.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-021-01607-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-021-01607-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qiu Guo & Hechun Liu & Faez M. Hassan & Mohammed Wasim Bhatt & Ahmed Mateen Buttar, 2022. "Application of UAV tilt photogrammetry in 3D modeling of ancient buildings," 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 424-436, March.
    2. Anshul Gupta & Pravin Srinath, 2022. "A recommender system based on collaborative filtering, graph theory using HMM based similarity measures," 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 533-545, March.
    3. Guoyong Wang & Lokanayaki Karnan & Faez M. Hassan, 2022. "Face feature point detection based on nonlinear high-dimensional space," 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 312-321, March.
    4. Wenzhong Xia & Rahul Neware & S. Deva Kumar & Dimitrios A. Karras & Ali Rizwan, 2022. "An optimization technique for intrusion detection of industrial control network vulnerabilities based on BP neural network," 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 576-582, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01607-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.