Scaling effectivity in manifold methodologies to detect driver’s fatigueness and drowsiness state

Gowrishankar Shiva Shankara Chari, Jyothi Arcot Prashant


The state of fatigueness and drowsiness relates to the stressed physical and mental condition of a driver that reduces the ability of a driver to drive safely leading to fatal consequences of road accidents. With a rising concerns about the road safety, the premium and modern vehicles are coming up with a sophisticated technology to detect and rise alarm during the positive case of fatigueness and drowsiness. Irrespective of availability of archives of literatures towards solving this problem, it is quite unclear about the strength and weakness of varied methodologies. Therefore, this paper presents a crisp and insightful discussion about the recent methodologies associated with detecting driver's attention, fatigueness, drowsiness along with highlights of commercial devices to realize various limiting factors and constraints associated with them. The paper contributes to introduce a well-structured flow of research trend to realize various patterns of current trend adopted towards solving varied problems and significant research gaps have been identified in this process. The outcome of this paper presents that still there is an open scope of an improvement towards accomplishing the agenda towards safer driving.


Accident; Driver; Drowsiness; Fatigueness; Vehicle

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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