This paper proposes a new design methodology for Intelligent Transportation Systems, which uses existing smart techniques in transportation systems and human behavior detections to counter lone wolf threats and driver violations. The design can be attached to vehicles as an intelligent embedded system. In this design, the electroencephalogram analysis techniques are used to detect the irregularity in driver behavior which can be categorized into threatened or violated behavior. In threaten behavior like deliberate run-over accidents, the system will stop the vehicle as soon as possible and inform the security agency to ensure a speed response. In violated behavior like driver drowsiness, the system will alert the driver or inform the responding authorities and stop the vehicle, depending on the level of danger. To minimize the consequences of the vehicle fast stopping, it proposed to green the next traffic light signs. By applying this system in vehicles a lot of accidents can be avoided, in particular those caused by lonely wolves like deliberate run-over accidents or stolen of vehicles.
Intelligent Transportation Systems, Internet of Things, Deliberate Run-Over Accidents, Berlin Attack, Lone Wolves Threats.
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Cite this paper
Hassan F. Morsi, M. I. Youssef, G. F. Sultan. (2017) Novel Design Based Internet of Things to Counter Lone Wolf Part B: Berlin Attack. International Journal of Mathematical and Computational Methods, 2, 235-242
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