IoT-based smart alert system for drowsy driver detection

Title

IoT-based smart alert system for drowsy driver detection

Creator

Biswal A.K.; Singh D.; Pattanayak B.K.; Samanta D.; Yang M.-H.

Description

In current years, drowsy driver detection is the most necessary procedure to prevent any road accidents, probably worldwide. The aim of this study was to construct a smart alert technique for building intelligent vehicles that can automatically avoid drowsy driver impairment. But drowsiness is a natural phenomenon in the human body that happens due to different factors. Hence, it is required to design a robust alert system to avoid the cause of the mishap. In this proposed paper, we address a drowsy driver alert system that has been developed using such a technique in which the Video Stream Processing (VSP) is analyzed by eye blink concept through an Eye Aspect Ratio (EAR) and Euclidean distance of the eye. Face landmark algorithm is also used as a proper way to eye detection. When the drivers fatigue is detected, the IoT module issues a warning message along with impact of collision and location information, thereby alerting with the help of a voice speaking through the Raspberry Pi monitoring system. Copyright 2021 Anil Kumar Biswal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Source

Wireless Communications and Mobile Computing, Vol-2021

Date

2021-01-01

Publisher

Hindawi Limited

Coverage

Biswal A.K., Department of CSE, ITER, SOA Deemed to be University, India; Singh D., Department of CSIT, ITER, SOA Deemed to be University, India; Pattanayak B.K., Department of CSE, ITER, SOA Deemed to be University, India; Samanta D., Department of Computer Science, CHRIST Deemed to be University, India; Yang M.-H., Department of Computer Science and Info. Engineering, National Central University, Taiwan

Rights

All Open Access; Gold Open Access

Relation

ISSN: 15308669

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1155/2021/6627217

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102518105&doi=10.1155%2f2021%2f6627217&partnerID=40&md5=5472c79a7eda55f40e4dc6fbdb9325e3