ACCIDENTS IN TUNNEL CLASSIFICATION USING DEEP LEARNING

This research presents an innovative approach to accident classification within tunnels using deep learning algorithms. Given the unique challenges posed by tunnel environments, such as limited visibility and confined spaces, effective accident detection is paramount for ensuring swift response and safety. Utilizing a dataset comprising various tunnel accidents, we trained and evaluated multiple deep learning models. Our results show a significant improvement in classification accuracy compared to traditional methods. The proposed system demonstrates potential for real-time monitoring and alerting in tunnel infrastructure, emphasizing the utility of deep learning in enhancing transportation safety in constrained environments.