Abstract
The National Highway Traffic Safety Administration (NHTSA) reports state that over 100,000 accidents and more than 1,000 deaths per year are related to drivers’ drowsiness. The situation becomes prone to an accident when either the driver is sleepy or accelerating, or is not able to see the course ahead due to weather conditions. Many types of research have been done in this area and several are ongoing to prevent this from happening. This paper will be focused on that plus gleaning acceptable accurate results. For a brief outlook: the images captured by the camera will go through mathematical calculation and machine learning to check if the driver is drowsy or not. It can be used to construct a real-time drowsiness detection system. The model made should be lightweight, should not require more space, and should provide good accuracy in results.
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Bhagat, D.P., Prajapati, B., Pawar, K., Parekh, D., Gandhi, P. (2023). Drowsiness Detection System. In: Choudrie, J., Mahalle, P.N., Perumal, T., Joshi, A. (eds) ICT for Intelligent Systems. ICTIS 2023. Smart Innovation, Systems and Technologies, vol 361. Springer, Singapore. https://doi.org/10.1007/978-981-99-3982-4_2
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DOI: https://doi.org/10.1007/978-981-99-3982-4_2
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