Manuscript Title:

VEHICULAR DISASTER IMPACT IDENTIFICATION USING DEEP LEARNING

Author:

Dr. S.K. MANJU BARGAVI, MARY JOSEPH, Dr. NAVEEN KUMAR G. N, Dr. THOMAS SAMRAJ LAWRENCE

DOI Number:

DOI:10.17605/OSF.IO/ECXWZ

Published : 2022-06-10

About the author(s)

1. Dr. S.K. MANJU BARGAVI - Professor, School of CS & IT, Jain (Deemed-to-be) University, Bangalore, India.
2. MARY JOSEPH - Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai.
3. Dr. NAVEEN KUMAR G N- Associate Professor, Electronics and Communication Engineering, CMR Institute of Technology Bengaluru.
4. Dr. THOMAS SAMRAJ LAWRENCE - Associate Professor, Department of Information Technology, College of Engineering and Technology, Dambi Dollo University.

Full Text : PDF

Abstract

The rapid growth of the civilization has made our lives easier and increases the auto vehicles usage to a great extent. With great increase in the usage of cars and automotive vehicles, chances of getting accidents are also very high. India needs to improve the way they respond to the road accidents this is a system that can help in the identifying the severity of the accident and detect the accident using deep learning and computer vision techniques. The project aims to monitor the accident in cities and to reduce the death rates. Nowadays, road accident rates are very high. Early detection and timely medical aid will help a lot in these situations. Regular traffic systems are implemented with cameras and installed in most of the town to watch and control traffic. A Smart City with an AI traffic monitoring and reporting mechanism, a more superior traffic monitoring method may recognize and discover moving objects like automobiles and motorbikes in live camera supports. Furthermore, detect collision of those moving objects and helps to provide an accurate location to the nearby center about the accident to supply immediate medical care and sends a message to the closest police headquarters.


Keywords

Deep Learning, OpenCV, Object Detection, Tensorflow, Traffic.