One of the leading causes of car accidents nowadays is dozing off behind the wheel. The National Highway Traffic Safety Administration estimates that around one hundred thousand crashes each year are caused by drivers who were too tired to operate their vehicles safely. According to the numbers, driver fatigue is a major contributor to car accidents, which in turn cause a disproportionately high number of fatalities. Several technologies have been developed to avoid accidents caused by drivers who are too sleepy or too tired to operate a vehicle safely. In the past, detecting driver sleepiness required the use of psychological tests. One main problem of this technology was that electrodes had to be attached to the user's scalp and skin. The purpose of this research was to develop an intelligent alert method for constructing autonomous cars free from the effects of driver fatigue. Yet, sleepiness is a normal human experience brought on by a variety of physiological and environmental variables. As a result, developing a reliable warning system to forestall the incident's root cause is essential. To combat driver fatigue and ensure safe travel, this article proposes integrating a payment module with a warning system. Drowsiness can be detected with the use of bio-indicators that scan the driver's face for telltale symptoms of fatigue and then sound an alarm. If the driver blinks their eyes and the health criteria are off, the alarm will sound. The suggested protocol enables the appointing bodies to levy the punishment for drowsy driving and transmit the private payment details to the mobile app. The consumer, the bank, and the retailer all participate in a safe session established by the application. Static analysis and informal security approaches both show that the proposed protocol is secure enough to be used for mobile payments.


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    Titel :

    An Automated Efficient and Robust Scheme in Payment Protocol Using the Internet of Things


    Beteiligte:


    Erscheinungsdatum :

    2023-04-06


    Format / Umfang :

    3540319 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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