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@article{149745,
        author = {Sneha  Chinathambi and Shivani.C.Jadhav and Snehal Sarwade and Kranti Kamble},
        title = {Detection of driver’s fatigue},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {7},
        number = {1},
        pages = {648-651},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=149745},
        abstract = {A number of approaches have been developed to reduce the risks of drowsy drivers. Almost all the statistics have identified driver drowsiness as a high priority vehicle safety issue. 
In our project we are using behavior- based approach mechanism for detecting driver’s fatigue. We are predicting fatigue or drowsiness by calculating Euclidean distance of eye and the Eye Aspect Ratio. 
There is an increased interest with respect to the design and advancement of computer controlled automotive applications to overcome those problems by enhancing safety to reduce accidents, increase traffic flow, and enhance comfort for drivers. 
Additionally, a number of technical aspects should be seriously considered, including correctly capturing face and eye characteristics from unwanted movements, unsuitable task environments, technological limitations, and individual differences.
},
        keywords = {EAR, Euclidean Distance, Haar Cascade, PERCLOS, Alcohol },
        month = {},
        }