Automatic Road Accident Detection Using Deep Learning

Accident detection plays an important role in ensuring road safety and providing an immediate response that can significantly reduce the loss of lives. A deep learning model is proposed for efficient accident detection. The initial phase involves the careful curation of a diverse dataset to train models that can autonomously recognize accidents, ensuring precise detection through rigorous optimization. Trained models, adapt at discerning nuances and trigger critical responses, including immediate alerts and coordination with emergency services, thereby enhancing effectiveness in critical situations. A crucial feature includes alerting via the Simple Mail Transfer Protocol (SMTP). In the event of an accident, the system seamlessly interfaces with SMTP, enabling swift communication and prompt notification to the emergency services. The proposed model provides an accuracy of 95%, representing a higher level of accuracy in detecting accidents. Thus, the integrated approach represents a significant leap in road accident detection.