Accident Detection in Live Surveillance

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Accident Detection in Live Surveillance

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Abstract

With the increase in number of vehicles in the country vehicle detection is an important in road traffic management system. Different traffic accident causes such as vehicle overspeeding, wrong way driving, collision and accident can be detected by CCTV installed on roads. The results obtained from traffic parameters can be applied for vehicle tracking, vehicle classification, parking area monitoring, road traffic monitoring and management etc. The main objective of this project is to decrease the deaths caused by accident occurring because over speeding, wrong war driving by ensuring public safety and also a building a better system for managing the traffic on the roads. The aim of this paper is to develop a system that can detect the vehicle accident which are caused by overspeeding, wrong way driving and collision detection on city roads. A prototype system is developed and tested. deep learning, heatmap, openCV, ROI, SSD model, tensor flow.

References

1 Cites in Article
  1. Unknown Title.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Shrey Gupta, Vandana Choudhary. 2019. "Accident Detection in Live Surveillance". Global Journal of Computer Science and Technology - H: Information & Technology GJCST-H Volume 19 (GJCST Volume 19 Issue H1).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
Classification
GJCST-H Classification J.7
Version of record

v1.2

Issue date
August 31, 2019

Language
English
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Accident Detection in Live Surveillance

Shrey Gupta
Shrey Gupta
Vandana Choudhary
Vandana Choudhary