research-article

Real-time driver drowsiness detection using wearable technology

Authors:

Mohammed Misbhauddin,

AlReem AlMutlaq,

Alaa Almithn,

Norah Alshukr,

Maryam AleesaAuthors Info & Claims

SCA '19: Proceedings of the 4th International Conference on Smart City Applications

Article No.: 94, Pages 1 - 6

https://doi.org/10.1145/3368756.3369081

Published: 02 October 2019 Publication History

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Abstract

Road accidents are a worldwide problem, consequences of which can lead to death. One of the reasons drivers experience near-miss or real accidents is because of drowsy driving. Drowsy driving is considered as a major problem that not only affects the driver but also threatens the life of others and cause damage to the country's infrastructure. In this paper, we propose a wearable-based solution that tracks the user's state of activeness and gives real-time feedback. Our proposed solution tracks and records the user's Heart Rate Variability and the Galvanic Skin Response to identify the user's state of activeness. The proposed mobile application interfaces with the wearable device to gather user data and perform analysis. If results are lower than the expected threshold, the user is informed by auditory feedback.

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Cited By

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Loni D(2024)Analysis of Facial and Acoustic Features for Driver Drowsiness Detection2024 International Conference on Intelligent Systems and Advanced Applications (ICISAA)10.1109/ICISAA62385.2024.10828958(1-7)Online publication date: 25-Oct-2024
https://doi.org/10.1109/ICISAA62385.2024.10828958
Perkins ESitaula CBurke MMarzbanrad F(2023)Challenges of Driver Drowsiness Prediction: The Remaining Steps to ImplementationIEEE Transactions on Intelligent Vehicles10.1109/TIV.2022.32246908:2(1319-1338)Online publication date: Feb-2023
https://doi.org/10.1109/TIV.2022.3224690
Mirabdullayev IAhamed Ayoobkhan MJasmine Hashana AKhan Subair Ali L(2023)Drowsy Driving Detection System Using Face Detection2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS)10.1109/ICTACS59847.2023.10390069(779-784)Online publication date: 1-Nov-2023
https://doi.org/10.1109/ICTACS59847.2023.10390069
Show More Cited By

Index Terms

Real-time driver drowsiness detection using wearable technology
1. Information systems
  1. Information systems applications
    1. Mobile information processing systems

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Information

Published In

SCA '19: Proceedings of the 4th International Conference on Smart City Applications

October 2019

788 pages

ISBN:9781450362894

DOI:10.1145/3368756

Editors:
Ben Ahmed Mohamed
UAE University-FST of Tangier, Morocco
,
İsmail Rakıp Karașo
Karabuk University, Turkey
,
Rachid Saadane
EHTP, Casablanca, Morocco
,
Wassila Mtalaa
Luxembourg Institute of Science and Technology
,
Boudhir Anouar Abdelhakim
UAE University-FST of Tangier, Morocco

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 02 October 2019

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SCA2019: The Fourth International Conference on Smart City Applications

October 2 - 4, 2019

Casablanca, Morocco

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Loni D(2024)Analysis of Facial and Acoustic Features for Driver Drowsiness Detection2024 International Conference on Intelligent Systems and Advanced Applications (ICISAA)10.1109/ICISAA62385.2024.10828958(1-7)Online publication date: 25-Oct-2024
https://doi.org/10.1109/ICISAA62385.2024.10828958
Perkins ESitaula CBurke MMarzbanrad F(2023)Challenges of Driver Drowsiness Prediction: The Remaining Steps to ImplementationIEEE Transactions on Intelligent Vehicles10.1109/TIV.2022.32246908:2(1319-1338)Online publication date: Feb-2023
https://doi.org/10.1109/TIV.2022.3224690
Mirabdullayev IAhamed Ayoobkhan MJasmine Hashana AKhan Subair Ali L(2023)Drowsy Driving Detection System Using Face Detection2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS)10.1109/ICTACS59847.2023.10390069(779-784)Online publication date: 1-Nov-2023
https://doi.org/10.1109/ICTACS59847.2023.10390069
Sowmyashree PSangeetha J(2023)Driver Drowsiness Detection System Based on Behavioral Method, Biological Method and Vehicular Feature-Based Method—A ReviewIntelligent Systems and Sustainable Computing10.1007/978-981-99-4717-1_12(125-134)Online publication date: 3-Oct-2023
https://doi.org/10.1007/978-981-99-4717-1_12
Tarafder SBadruddin NYahya NNasution A(2022)Drowsiness Detection Using Ocular Indices from EEG SignalSensors10.3390/s2213476422:13(4764)Online publication date: 24-Jun-2022
https://doi.org/10.3390/s22134764
Saleem ASiddiqui HRaza MRustam FDudley SAshraf I(2022)A systematic review of physiological signals based driver drowsiness detection systemsCognitive Neurodynamics10.1007/s11571-022-09898-917:5(1229-1259)Online publication date: 22-Oct-2022
https://doi.org/10.1007/s11571-022-09898-9

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Recommendations

The Potential of Wrist-Worn Wearables for Driver Drowsiness Detection: A Feasibility Analysis

Vehicle driver drowsiness detection method using wearable EEG based on convolution neural network

Real-Time V2V Communication With a Machine Learning-Based System for Detecting Drowsiness of Drivers

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