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@article{151675,
        author = {Sarthak Mishra and Saurabh Mishra and Prajwal Verma and Saif},
        title = {Driver Drowsiness Detection System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {451-454},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151675},
        abstract = {Machine learning techniques have been used in order to predict the condition and emotion of a driver to provide information that will improve safety on the road. It is and application of artificial intelligence. Artificial Intelligence is a method by which systems can automatically learn as well as improve without being explicitly programmed. A driver’s condition can be estimated by bio-indicators, behavior while driving as well as the expressions on the face of a driver. In this paper we present an all-inclusive survey of recent works related to driver drowsiness detection and alert system. We also present the various machine learning techniques such as PERCLOS algorithm, HAAR based cascade classifier,  OpenCV which are used in order to determine the driver’s condition. Finally, we identify the challenges faced by the current systems and present the corresponding research opportunities.},
        keywords = {Artificial Intelligence, Autonomous Vehicle
Technology, Drowsiness Detection, Machine Learning.
},
        month = {},
        }