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Exploitation of Data Mining to Analyse Realistic Facts from Road Traffic Accident Data

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • Namita Gupta

    (Mahatma Jyoti Rao Phoole University)

  • Dinesh Kumar Saini

    (Sohar University)

Abstract

Accident data is often recorded more for the sake of updating record books and for creating statistical information rather than, as a source of intelligence. As most prior studies have been persistent on a few risk factors, some specific road users, or certain types of accidents, many significant factors affecting injury or sternness of the collision have not been completely identified as yet. The fundamental stipulation for recuperating road security is to attain and analyze a comprehensive road catastrophe database. An advanced road accident analysis system is needed to help develop a road safety initiative strategy as well as to instil a better understanding of road traffic accidents. Data mining has the potential to abolish paucity related to road traffic accidents as well as statistical constraints. In this paper, we analyze data extraction methods, which can be applied to arrive at some new, intangible, and reasonable facts from road traffic accident data.

Suggested Citation

  • Namita Gupta & Dinesh Kumar Saini, 2020. "Exploitation of Data Mining to Analyse Realistic Facts from Road Traffic Accident Data," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 847-853, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_85
    DOI: 10.1007/978-3-030-41862-5_85
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