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A Deep Learning-Based Car Accident Detection Framework Using Edge and Cloud Computing

Year: 2024

Type: article

Abstract: The evolving technological landscape has seen a pivotal shift with the advent of edge computing, transforming various sectors, particularly accident detection. Edge computing enhances road safety by enabling realtime data processing from onboard sensors, cameras, and connected devices, addressing limitations in traditional cloudbased systems. This paper introduces a deep learning-based accident detection framework within an edge-cloud setup. Utilizing a CNN model, accidents are detected at the edge node near the data source, ensuring low latency, reduced network usage, and faster execution times. The model achieves a remarkable 95.91% accuracy.

Source: International Journal of Innovative Research in Computer and Communication Engineering

DOI: 10.15680/ijircce.2024.1210059

Authors: Mala . K, Monisha . T N

Language: English

Topic: IoT and GPS-based Vehicle Safety Systems

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: diamond

OpenAlex ID: W4403875255

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