Real-Time Accident Detection in Traffic Surveillance (Pr/5)

Overview

The Real-Time Accident Detection in Traffic Surveillance project leverages deep learning (CNN) and Python to detect traffic accidents in real-time. This system aims to enhance road safety by enabling rapid emergency response, minimizing casualties, and reducing the impact of road accidents. This innovative approach addresses the challenges of increasing vehicle numbers and accidents, particularly in high-risk regions.

Completion Date

May 2024

Tools and Technologies

Deep Learning, Convolutional Neural Networks (CNN), Python, Jupyter Notebook

Keywords

Real-Time Detection, Traffic Surveillance, Accident Detection, Deep Learning, CNN, Emergency Response, Road Safety

Dataset

Video file: Accidents-1.mp4

Installation

1. Clone the repository

https://github.com/Adnans-Design-Niche/ML-03.git

2. Run the Jupyter Notebook

Presentation

https://tome.app/adnans-home/real-time-accident-detection-in-traffic-surveillance-using-deep-learning116-135-clw62yyyw01bkmr5x4ly9q2bu

Contributors

Mohammed Adnan Siddiqui Raj Kumar Reddy