Intelligent Driver Monitoring System for Safe Driving

Q3 Engineering

AUS Pub Date : 2023-03-29 DOI:10.1109/ESARS-ITEC57127.2023.10114838

Adarsh Vijay

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引用次数: 0

Abstract

More than 80 percent of collisions will result from the driver's negligence brought on by drunkenness and drowsiness. Numerous monitoring systems based on machine learning are being included in some cars. All these innovations are made in new automobiles as technology advances at a supersonic rate but leave a lot of empty spaces in each breakthrough. However, no single mechanism is now in place to assess the driver's identification, level of intoxication, and drowsiness. So this paper proposes a feasible system for monitoring real-time driver's wellness: “Intelligent driver monitoring System for safe driving” which gives suitable warnings and notifications to the user and the authority if necessary. This system includes authentication of the user followed by Drunkenness detection and Drowsiness detection. The user can interact with the Graphical user interface and the camera provided in the automobile frequently monitors the driver using Machine learning and neural network techniques, this checking method is implemented. This multi-model system uses many layers in Convolution neural network model and 92 percent accuracy is shown throughout the testing phase so that this system can replace any existing system which is only based on single models.

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安全驾驶智能驾驶员监控系统

80%以上的交通事故是由于醉酒和困倦导致的司机疏忽造成的。许多基于机器学习的监控系统被安装在一些汽车上。所有这些创新都是在新汽车上实现的，因为技术以超音速发展，但每次突破都会留下很多空白。然而，目前还没有单一的机制来评估司机的身份、醉酒程度和困倦。因此，本文提出了一种可行的实时监控驾驶员健康的系统:“安全驾驶智能驾驶员监控系统”，该系统在必要时向用户和当局发出适当的警告和通知。该系统包括用户认证、醉酒检测和困倦检测。用户可以与图形用户界面进行交互，汽车提供的摄像头利用机器学习和神经网络技术对驾驶员进行频繁监控，实现了这种检测方法。该多模型系统使用多层卷积神经网络模型，在整个测试阶段显示出92%的准确率，因此该系统可以取代任何仅基于单一模型的现有系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

AUS Engineering-Architecture

CiteScore

0.40

自引率

0.00%

发文量

期刊介绍： Revista AUS es una publicación académica de corriente principal perteneciente a la comunidad de investigadores de la arquitectura y el urbanismo sostenibles, en el ámbito de las culturas locales y globales. La revista es semestral, cuenta con comité editorial y sus artículos son revisados por pares en el sistema de doble ciego. Periodicidad semestral.