AI-powered Approach for Accident Occurance Alerting from Traffic Surveillance

Authors

  • S. Samreen
  • B. Poojitha
  • B. Pravalika

DOI:

https://doi.org/10.46243/jst.2023.v8.i12.pp156-167

Keywords:

Accident occurrence, Traffic Surveillance, AI, CNN.

Abstract

Accidents have been a major cause of deaths in India. More than 80% of accident-related deaths occur not due to the accident itself but the lack of timely help reaching the accident victims. In highways where the traffic is light and fast-paced an accident victim could be left unattended for a long time. The intent is to create a system which would detect an accident based on the live feed of video from a CCTV camera installed on a highway. The idea is to take each frame of a video and run it through a deep learning convolution neural network model which has been trained to classify frames of a video into accident or non-accident. Convolutional Neural Networks has proven to be a fast and accurate approach to classify images. CNN based image classifiers have given accuracy's of more than 95% for comparatively smaller datasets and require less preprocessing as compared to other image classifying algorithms.

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Published

2023-12-15

How to Cite

S. Samreen, B. Poojitha, & B. Pravalika. (2023). AI-powered Approach for Accident Occurance Alerting from Traffic Surveillance. Journal of Science & Technology (JST), 8(12), 156–167. https://doi.org/10.46243/jst.2023.v8.i12.pp156-167

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