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Improving Road Safety for Driver Malaise and Sleepiness Behind the Wheel Using Vehicular Cloud Computing and Body Area Networks

Improving Road Safety for Driver Malaise and Sleepiness Behind the Wheel Using Vehicular Cloud Computing and Body Area Networks

Meriem Benadda, Ghalem Belalem
Copyright: © 2020 |Volume: 12 |Issue: 4 |Pages: 23
ISSN: 1942-9045|EISSN: 1942-9037|EISBN13: 9781799806127|DOI: 10.4018/IJSSCI.2020100102
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MLA

Benadda, Meriem, and Ghalem Belalem. "Improving Road Safety for Driver Malaise and Sleepiness Behind the Wheel Using Vehicular Cloud Computing and Body Area Networks." IJSSCI vol.12, no.4 2020: pp.19-41. http://doi.org/10.4018/IJSSCI.2020100102

APA

Benadda, M. & Belalem, G. (2020). Improving Road Safety for Driver Malaise and Sleepiness Behind the Wheel Using Vehicular Cloud Computing and Body Area Networks. International Journal of Software Science and Computational Intelligence (IJSSCI), 12(4), 19-41. http://doi.org/10.4018/IJSSCI.2020100102

Chicago

Benadda, Meriem, and Ghalem Belalem. "Improving Road Safety for Driver Malaise and Sleepiness Behind the Wheel Using Vehicular Cloud Computing and Body Area Networks," International Journal of Software Science and Computational Intelligence (IJSSCI) 12, no.4: 19-41. http://doi.org/10.4018/IJSSCI.2020100102

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Abstract

Malaise and sleepiness behind the wheel are considered to be the leading causes of fatal highway accidents. With the body area networks (BANs), a continuous health monitoring of a driver can be performed without any constraint on his/her normal daily life activities. Many of the systems proposed in the literature are intended to prevent traffic accidents but without treating this kind of cause because difficult to highlight in an accident. This paper proposes “HAaaS,” a new vehicular cloud computing service based on BANs to detect, monitor, and manage driver malaise and provide a cooperation support for the driver rescue. The objective is to reduce the number of accidents, the material and human damage as the time and fuel lost in traffic jams. The proposed service has been validated by simulating real-world highway scenarios extracted from Oran city in Algeria. The results show that the service is efficient at a significant rate.

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