According to “The National Highway Traffic Safety Administration of the United States of America” drowsy driving was responsible for 72,000 crashes, 44,000 injuries and 800 deaths in 2013. With growing population and raise in the standards of living globally, there is an exponential increase in the automotive population. There are a number of concerning issues winding around this global trend, one among such dire issues is life loss caused by careless driving habits like intentional or unintentional drowsy driving. There may be a number of reasons for sleepiness or fatigue ranging from a general cause like lack of sleep to various medical causes like sleep disorders or medications. Considering the potential threat, we put forward a driver monitoring model using the facial land marks of the subject to determine the eye aspect ratio (EAR) and the mouth aspect ratio (MAR) to judge the consciousness of the motorist as a measure to sense and take appropriate action to control any deleterious outcomes.
Full Length Driver Drowsiness Detection Model—Utilising Driver Specific Judging Parameters
Smart Innovation, Systems and Technologies
2020-02-15
8 pages
Article/Chapter (Book)
Electronic Resource
English
Eye aspect ratio (EAR) , Mouth aspect ratio (MAR) raspberry pi , Computer vision , Python , Adaptive threshold setting , Image processing , Dynamic facial land marking Manufacturing, Machines, Tools, Processes , Sustainable Architecture/Green Buildings , Artificial Intelligence , Energy Systems , Engineering , Energy Materials
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