• Aarti Basawraj Swami
• Shrikant Shinde
• Snehal Birajdar
• Vishal Patil
• Vaishnavi Kshirsagar

Neural networks play a crucial role in accident detection by providing a powerful tool for processing and analyzing various types of data relevant to accidents. With population growth, the demand for vehicles has increased tremendously, which has created an alarming situation in terms of traffic hazards and road accidents. The road accidents percentage is growing exponentially and so are the fatalities caused due to accidents. However, the primary cause of the increased rate of fatalities is due to the delay in emergency services. Many lives could be saved with efficient rescue services. The delay happens due to traffic congestion or unstable communication to the medical units. The implementation of automatic road accident detection systems to provide timely aid is crucial. Many solutions have been proposed in the literature for automatic accident detection and various machine learning techniques. With such high rates of deaths associated with road accidents, road safety is the most critical sector that demands significant exploration. In this paper, we present a critical analysis of various existing methodologies used for predicting and preventing road accidents, highlighting their strengths, limitations and challenges that need to be addressed to ensure road safety and save valuable lives. A Convolutional Neural Network (CNN) is a type of artificial intelligence model that's particularly good at processing and analyzing visual data, such as images and video. In our proposed system, we implemented a vehicle accident detection using convolutional neural networks (CNN) to detect road accidents in inhabited areas, highways. CNNs have been applied to various fields, including automatic accident detection systems, to improve road safety. In the context of automatic accident detection systems, CNNs can be used to analyze images or video footage from cameras installed on roads and vehicles.

Video Detection, Convolutional Neural Network, Feature extraction, Accident detection, Road safety.

"An Automatic Vehicle Accident Detection using Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.f425-f431, May-2024, Available :http://www.jetir.org/papers/JETIR2405548.pdf

"An Automatic Vehicle Accident Detection using Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppf425-f431, May-2024, Available at : http://www.jetir.org/papers/JETIR2405548.pdf