Edge Computing And NLP In AI -Enabled Vehicle Emergency Systems: Reducing Response Time And Saving Lives

Authors

  • Donthabhaktuni Rama Krishna Upendra Prasad Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra Pradesh, Guntur, 522502, India
  • Kodukula Subramanyam Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra Pradesh, Guntur, 522502, India
  • D.Naga Malleswari Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra Pradesh, Guntur, 522502, India

DOI:

https://doi.org/10.63278/mme.vi.1584

Keywords:

Artificial Intelligence, Emergency Response Systems, Vehicle Safety, Deep Learning, Internet of Vehicles, Natural Language Processing, Edge Computing, Crash Detection, Emergency Resource Optimization, Injury Prediction.

Abstract

This paper presents a novel AI-driven emergency response system for vehicles that significantly improves post-crash emergency assistance by enhancing accident detection accuracy and response time optimization. The proposed system integrates multi-modal sensor data with deep learning techniques to accurately detect accidents, assess injury severity, and optimize emergency resource allocation. Experimental results demonstrate a 94.7% accuracy in crash detection, 89.3% accuracy in injury severity prediction, and an average 8.2-minute reduction in emergency response time compared to traditional systems. The framework incorporates vehicle sensor networks, edge computing, and natural language processing to create a comprehensive emergency response ecosystem. Field tests conducted across diverse environmental conditions validate the system's robustness and reliability, suggesting significant potential for reducing road traffic fatalities through AI-enhanced emergency response mechanisms.

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How to Cite

Prasad, Donthabhaktuni Rama Krishna Upendra, Kodukula Subramanyam, and D.Naga Malleswari. 2025. “Edge Computing And NLP In AI -Enabled Vehicle Emergency Systems: Reducing Response Time And Saving Lives”. Metallurgical and Materials Engineering, May, 311-36. https://doi.org/10.63278/mme.vi.1584.

Issue

Vol. 31 No. 5 (2025)

Section

Research

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Copyright (c) 2025 Donthabhaktuni Rama Krishna Upendra Prasad, Kodukula Subramanyam, D.Naga Malleswari

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