利用深度学习进行实时事故检测和救护车救援

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-05-11 DOI:10.48175/ijarsct-18188

Dr. P. U. Anitha, M. Akshay Kumar, T. Srinivas, M. Rakesh, M. Kalpana, K. Sushmitha

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引用次数: 0

摘要

交通事故对全球安全构成重大威胁。一种综合方法利用机器学习框架、深度学习技术和 Python 模块来减少伤亡和减轻损失。该系统利用谷歌 API 位置服务进行精确的地理位置跟踪，提高了事故预测的准确性。它还能根据位置和交通模式动态分配救护车，从而提高救护车调度效率。

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Real Time Accident Detection and Ambulance Rescue using Deep-Learning

Traffic accidents pose a significant threat to global safety. A comprehensive approach uses machine learning frameworks, deep learning techniques, and Python modules to reduce casualties and mitigate damage. The system uses Google API location services for precise geolocation tracking and improves accident prediction accuracy. It also enhances ambulance dispatching efficiency by dynamically assigning ambulances based on location and traffic patterns

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来源期刊

International Journal of Advanced Research in Science, Communication and Technology

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