A smart system for driver's fatigue detection, remote notification and semi-automatic parking of vehicles to prevent road accidents

Hossan, Alamgir; Kashem, Faisal Bin; Hasan, Md. Mehedi; Naher, Sabkiun; Rahman, Md. Ismail

doi:10.1109/meditec.2016.7835371

Cited by 15 publications

(4 citation statements)

References 18 publications

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“…Previous studies showed that a persistent auditory stimulus can cause mental fatigue and decreased alpha power in frontal regions [81], [82]. In addition, delta power increased, but alpha power decreased, during mental fatigue [83]. We also found that delta wPLI increased only in the low arousal group following auditory stimuli.…”

Section: Discussionsupporting

confidence: 70%

Frontal EEG Asymmetry of Emotion for the Same Auditory Stimulus

2020

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Emotions play an important role in human interaction and decision-making processes. Frontal asymmetry in brain activity is a promising neurophysiological indicator of emotion. Emotions are psychologically explained by the valence-arousal model, but as yet, frontal asymmetry has not been fully explained by this model. In this study, we explored frontal asymmetry of emotions based on the valence-arousal model using the same auditory stimulus. Changes in emotional states using self-report questionnaires were investigated before and after the auditory stimulus. Spectral power and weighted phase lag index were calculated in the delta, theta, alpha, beta, and gamma bands. Phase-amplitude coupling was also measured to explore communication among different frequency bands associated with emotions. After the auditory stimulus, alpha power decreased in both left and right frontal regions and the deltaweighted phase lag index in the left-right regions was increased. However, no frontal asymmetry was identified after the auditory stimulus. Additionally, we explored the brain changes according to the valencearousal model based on emotional states. After the auditory stimulus, frontal asymmetry of alpha power was clearly observed only for negative valence. This finding was possible because subjective emotions were considered despite listening to the same stimulus. Finally, phase-amplitude coupling identified lefthemisphere dominance after the auditory stimulus, regardless of subjective emotions. These results may help us understand frontal asymmetry associated with emotional mechanisms. In addition, these findings can be used directly in the brain-computer interface to improve emotion recognition performance for realworld practical applications. INDEX TERMS Electroencephalogram (EEG), Emotion, Frontal asymmetry, Power spectral density (PSD), Weighted phase lag index (WPLI), Phase-amplitude coupling (PAC).

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Section: Discussionsupporting

confidence: 70%

Frontal EEG Asymmetry of Emotion for the Same Auditory Stimulus

2020

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“…When the lane is not clearly visible or erased, a camera can be used to monitor the driver by looking for signs of fatigue. The driver is alerted by a sound signal and a flashing message in the control panel of the vehicle [ 81 , 82 ]. Some authors have proposed the use of EEG sensor and Artificial Intelligence (AI) to detect fatigue in the driver by analyzing the EEG brain signals changes through intelligent algorithms to detect abnormal conditions [ 83 , 84 ].…”

Section: Taxonomy Of Its Applicationsmentioning

confidence: 99%

Sensor Technologies for Intelligent Transportation Systems

Ibáñez

Zeadally

Contreras-Castillo

2018

Sensors

472

200

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Modern society faces serious problems with transportation systems, including but not limited to traffic congestion, safety, and pollution. Information communication technologies have gained increasing attention and importance in modern transportation systems. Automotive manufacturers are developing in-vehicle sensors and their applications in different areas including safety, traffic management, and infotainment. Government institutions are implementing roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. By seamlessly integrating vehicles and sensing devices, their sensing and communication capabilities can be leveraged to achieve smart and intelligent transportation systems. We discuss how sensor technology can be integrated with the transportation infrastructure to achieve a sustainable Intelligent Transportation System (ITS) and how safety, traffic control and infotainment applications can benefit from multiple sensors deployed in different elements of an ITS. Finally, we discuss some of the challenges that need to be addressed to enable a fully operational and cooperative ITS environment.

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“…These data are then integrated with the report and monitoring process [6][7]. Several research results prove that monitoring the health and fitness condition of drivers based on IoT can progress the efficiency of the transportation business, cut the cost of driver health care and reduce the risk of road accidents [5] [8][9][10][11][12][13]. Health services that are integrated into vehicles are certainly a challenge for developers as well as users [14].…”

Section: Introductionmentioning

confidence: 99%

Design of Health Monitoring Framework Model using oneM2M Standard

Adriansyah

Amrullah

2021

IJEEPSE

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The causes of traffic accidents are affected by human factors. Driver’s illness, such as exhaustion, drowsiness, and other chronic diseases, are the critical reasons for this. The creation of the Internet of Things (IoT) technology has tried to resolve these issues. The emphasis is on tracking and regulating driving safety and conditions. Unfortunately, there is no uniform IoT standard for this device. This study aims to provide a model for monitoring and handling the situation of drivers by combining the E-Health Tracking (EHM) and the Automotive Health and Safety (AHS) frameworks. The results of the system design are referred to as In-vehicle E-Health Monitoring (IV-EHM). The IV-EHM framework model analysis based on the oneM2M standard has been carried out. Based on the study, it can be said that the system has the specified requirements.

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A smart system for driver's fatigue detection, remote notification and semi-automatic parking of vehicles to prevent road accidents

Cited by 15 publications

References 18 publications

Frontal EEG Asymmetry of Emotion for the Same Auditory Stimulus

Frontal EEG Asymmetry of Emotion for the Same Auditory Stimulus

Sensor Technologies for Intelligent Transportation Systems

Design of Health Monitoring Framework Model using oneM2M Standard

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