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Road accidents persist as a critical global concern, resulting in substantial loss of life and economic burden. This research paper delves into the underlying causes of these accidents, which often stem from a multitude of factors including weather conditions, road surface conditions, and driver behavior. Leveraging machine learning algorithms and data visualization tools, we have developed a predictive model that identifies accident severity. The system integrates real-time weather data, providing a dynamic and comprehensive view of road conditions. By accurately forecasting accident severity, we aim to significantly reduce response times for emergency services and enhance overall traffic safety. This paper provides an overview of our approach, detailing the technologies employed and their potential impact on mitigating the pervasive issue of road accidents.
Singh et al. (Fri,) studied this question.